arxiv
Score 37.0
2026-06-29 · Byeong Hoon Yoon
Research Track A · General AI
We introduce Neural Subspace Reallocation (NSR), which reframes continual learning as memory management over parameter subspaces. Instead of treating Low-Rank Adaptation (LoRA) modules as disposable per-task adapters, NSR manages them as compressible, retrievable memory units on a frozen backbone through a recurring cy…
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arxiv
Score 27.0
2026-06-29 · Bertram Taetz, Hugo Albuquerque Cosme da Silva, Gabriele Bleser-Taetz
Research Track A · General AI
Motion-language agents must possess the bidirectional capability to both understand human movement (motion-to-text, M2T) and generate it from natural language (text-to-motion, T2M). While foundational models have achieved strong performance in static settings, autonomous agents operating in dynamic environments must co…
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arxiv
Score 24.5
2026-06-29 · Xuan Zhao, Haonan He, Qingyu Yang, Minglei Li, Jingqi Ye, Zelin Tan, Bo Wan, Peng Ye
Research Track A · General AI
Since intelligence fundamentally relies on efficient skill acquisition (Chollet, 2019), the ability to leverage skills is critical. For LLMs, skills, manually authored or extracted from task trajectories, are textual recipes encoding mature problem-solving experience and are critical to agentic capabilities. Despite wi…
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arxiv
Score 22.8
2026-06-29 · Xuan Zhang, Wenxuan Zhang, See-Kiong Ng, Yang Deng
General AI
World models offer a principled way to equip long-horizon LLM agents with foresight: predictions of action consequences before execution. However, unreliable foresight can be ignored, misused, or even degrade downstream decision-making. In this paper, we introduce WorldEvolver, a self-evolving world model framework tha…
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- unreviewed
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arxiv
Score 22.4
2026-06-25 · Tianyi Men, Zhuoran Jin, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao
Research Track B · General AI
Multimodal web agents can assist humans in operating repetitive GUI tasks, where effective task planning is essential for decomposing complex tasks into executable actions. While small open source MLLMs are cost efficient and privacy preserving compared with commercial large models, they suffer from weak planning and l…
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- pending
- Role
- unreviewed
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arxiv
Score 21.5
2026-06-29 · Yiting Hu, Lingjie Duan, Qian Zhang
Research Track A
Machine unlearning aims to eliminate the influence of specific data from trained models to safeguard privacy. However, this presents a significant challenge in the context of continual learning (CL), where models update sequentially on dynamic datasets. A major limitation is that current certified unlearning algorithms…
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arxiv
Score 19.8
2026-06-27 · Dianwei Chen, Yuan-Zheng Lei, Zifan Zhang, Yuchen Liu, Xianfeng, Yang
General AI
Recent advancements in generative artificial intelligence (AI) and large language models (LLMs) have shown significant promise in automating complex reasoning, summarization, and question-answering tasks. However, the effectiveness of general-purpose LLMs in specialized engineering domains remains limited due to insuff…
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arxiv
Score 19.8
2026-06-29 · Haocong He, Chenfei Liao, Zichen Wen, Zihao Dongfang, Xu Zheng, Bin Ren, Chang Su, Zixin Zhang, Harold Haodong Chen, Hongfei Zhang, Weijia Li, Kailun Yang, Conghui He, Xuming Hu, Nicu Sebe, Linfeng Zhang
General AI
Multimodal Large Language Models (MLLMs) have demonstrated promising spatial reasoning capabilities, while these abilities remain underexplored in the emerging visual modality of panoramic imagery. The full 360°$\times$180° field of view of panoramas essentially supports complex global multi-step reasoning, which is al…
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- unreviewed
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arxiv
Score 19.4
2026-06-24 · Zhihao Gu, Lin Wang
Research Track A · General AI
Building a generalist robot that can leverage prior knowledge for continuous task adaptation remains a significant challenge. Previous works alleviate the catastrophic forgetting problem by parameter-efficient fine-tuning for single-task adaptation. However, they fail to extract reusable skills and model the interactio…
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huggingface
Score 19.4
2026-06-26 · Shoufa Chen, Luyuan Wang, Xuan Yang, Zhiheng Liu, Yuren Cong, Yuanfeng Ji, Feiyan Zhou, Xiaohui Zhang, Fanny Yang, Belinda Zeng
General AI
As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader range of general computer-use tasks beyond coding. However, existing benchmarks do not adequately evaluate general-purpose terminal computer-use agents (TUAs): general comp…
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huggingface
Score 19.4
2026-06-26 · Hohin Kwan, Hongyu Li, Ray Zhang, Manyuan Zhang, Xianghao Kong, Anyi Rao, Jiahao Xie, Si Liu
General AI
Recent interest in multimodal large language models (MLLMs) raises a central question: can they reason over dynamic visual evidence rather than merely recognize objects or events in individual frames? This ability, which we refer to as video temporal-logical reasoning, requires models to maintain, update, and compose e…
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arxiv
Score 18.8
2026-06-29 · Yuhan Zhang, Zhiyuan Guo, Ziheng Zeng, Wei Wang, Wentao Wu, Lijie Xu
General AI
Long-term conversational agents need to remember and query cross-session, multi-typed information with complex correlations. Existing agent memory systems rely on heterogeneous vector and graph databases, which fragment memory information and cause high cross-database I/O latency. For retrieval, common RAG-style method…
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arxiv
Score 18.8
2026-06-29 · Haoyang Li, Guanlin Li, Youhe Feng, Chen Zhao, Zhuoran Wang, Yang Li, Qizhe Wei, Shifeng Bao, Haitao Shen, Yihan Zhao, Tong Yang, Jing Zhang
General AI
Cross-embodiment transfer in vision-language-action (VLA) models remains challenging because low-level state and action spaces differ fundamentally across robot platforms. We observe that the high-level cognitive process underlying manipulation, including scene perception, object identification, task planning, and sub-…
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- unreviewed
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arxiv
Score 18.0
2026-06-29 · Haoliang Han
Research Track A · General AI
Long-running language agents need mechanisms for deciding which experiences should persist after the working context is gone. Retrieval systems can reinsert past text, but they do not by themselves show that an experience has been selectively consolidated into the model's own behavior. We introduce EVAF, an Echo-Valenc…
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- pending
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- unreviewed
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huggingface
Score 17.2
2026-06-28 · Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong, Weiming Wu, Jiayang Sun, Jiamin Song, Kaiqian Cui, Bowen Wang, Haoyuan Wu, Yitong Li, Dunjie Lu, Haikong Lu, Qi Zhen, Xinyuan Wang, Jiaqi Deng, Yuhao Yang, Cheng Chen, Boyuan Zheng, Alex Su, Xiao Yu, Hao Zou, Saaket Agashe, Xing Han Lu, Manpreet Kaur, Zhengyang Qi, Vincent Sunn Chen, Frederic Sala, Dayiheng Liu, Junyang Lin, Zhou Yu, Yu Su, Siva Reddy, Xin Eric Wang, Peng Qi, Tianbao Xie, Tao Yu
Research Track B · General AI
Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of frontier agents. We introduce OSWorld 2.0, a benchmark of 108 long-horizon computer-use workflows across everyday and professional tasks, des…
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- unreviewed
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arxiv
Score 15.8
2026-06-29 · Cao-Tri Nguyen, Nguyen-Khoa Luong, Vinh-Tiep Nguyen, Minh-Triet Tran
General AI
Photographs frequently contain \emph{visual distractors} besides foregrounds and backgrounds of the intended subject, competing for attention and weakening composition. While modern editing tools streamline object removal, identifying which objects to remove remains a mostly manual process. Existing saliency models and…
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arxiv
Score 15.5
2026-06-29 · Rahul Khedar, Mayank Malhotra, Avinash Karn, Mouli V, Prakhar Mehrotra
Research Track B · General AI
Live product demonstrations are a recurring, high-cost activity in software organizations: a human presenter must select features, dispatch the corresponding interactions on a running application, narrate them coherently, and answer questions in real time. Existing automation addresses only fragments -- generalist brow…
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- unreviewed
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arxiv
Score 15.0
2026-06-29 · Naeem Paeedeh, Mahardhika Pratama, Wolfgang Mayer, Mukesh Prasad, Weiping Ding, Yew-Soon Ong
Research Track A · General AI
Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem in the case of data scarcity. This paper puts forward a relatively uncharted problem, namely, few-shot domain incremental learning (FSDIL), taking into account the probl…
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arxiv
Score 14.8
2026-06-29 · Yuhong Deng, Yuyao Liu, David Hsu
General AI
Can the robot use a plate to cut a cake if no knife is available? Tool use greatly expands robot capabilities, but to use tools creatively beyond their intended functions, the robot faces the challenge of $\textit{open-world affordance grounding}$: select an open-category object to act as a tool and localize its specif…
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arxiv
Score 14.8
2026-06-29 · Jiamei Jiang, Jiajing Zhang, Feifei Mo, Linjing Li, Daniel Zeng
General AI
Planning often requires symbolic specifications that are both executable and verifiable. For large language models deployed in autonomous or decision-support systems, failures in such formalization may lead to unverifiable decisions, execution failures, or unsafe downstream behavior. We present NL-PDDL-Bench, a multi-d…
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arxiv
Score 14.0
2026-06-28 · Alex Kwon
Research Track A · General AI
LLM agents carry conclusions across steps and sessions in compressed memory, and memory products (e.g., mem0, LangMem) rewrite conversation into stored "facts" that later steps trust. We show this rewriting manufactures confidence: across our constructed agent settings, a casual, hedged remark becomes a confident, date…
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arxiv
Score 13.8
2026-06-29 · Cheng Gong, Haoyang Wang, Chao Lu, Zirui Li, Jianwei Gong
Research Track A · General AI
Autonomous driving policies should be able to improve continually as deployment exposes them to increasingly diverse and long-tail traffic situations. However, most learning-based policies are trained or fine-tuned on expert demonstrations and then rely largely on generalization to handle challenging closed-loop scenar…
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arxiv
Score 13.8
2026-06-29 · Nico Daheim, Iryna Gurevych
General AI
With rapidly improving capabilities, Large Language Models (LLMs) are increasingly used in many complex real-world tasks. Beyond requiring in-depth knowledge and reasoning skills, many of these tasks exhibit a high degree of subjectivity and require that the outputs of the model can be trusted. While a lot of progress …
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- unreviewed
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arxiv
Score 13.4
2026-06-25 · Zhongxin Guo, Danrui Qi, Hanwen Gu, Peng Cheng, Yongqiang Xiong
Research Track B · General AI
Agents often repeatedly solve similar task instances from scratch, leading to unnecessary reasoning cost and long execution traces. Prior work has explored workflow reuse and executable skill induction, but it remains unclear which task scenarios admit procedural skills and how the shared procedural structure should be…
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huggingface
Score 13.0
2026-06-27 · Han Luo, Bingbing Wen, Lucy Lu Wang
General AI
LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is well specified or achievable in the available environment. In such cases, a reliable agent should recognize that further interaction is unlikely to help and abstain fro…
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arxiv
Score 13.0
2026-06-29 · Matan Schliserman, Gon Buzaglo, Itay Evron, Daniel Soudry
Research Track A
We characterize weakly regularized continual classification in homogeneous models as sequential projections onto task margin sets. This result generalizes prior analyses restricted to either stationary (single-task) deep models or continual linear models. We show that global convergence generally fails, even for simple…
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arxiv
Score 12.8
2026-06-29 · Asif Shahriar, Hongyu Cai, Hadjer Benkraouda, Gang Wang, Z. Berkay Celik
General AI
Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs are susceptible to the same cognitive heuristics that bias human judgment. Yet, no work has investigated whether these heuristics affect a model's assessment of code vulne…
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huggingface
Score 12.0
2026-06-29 · Jiacheng Zhang, Haoyu He, Sen Zhang, Shen Wang, Xiaolei Xu, Yuhao Sun, Meng Shen, Feng Liu
General AI
In real-world applications, guardrails are often expected to identify unsafe user-model interactions according to application-specific safety policies, rather than relying on predefined risk taxonomies. In this work, we study this setting under the paradigm of in-context policy guardrailing, where guardrails predict sa…
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arxiv
Score 11.9
2026-06-25 · Minbyul Jeong
Research Track B · General AI
Web-agent benchmarks overwhelmingly measure depth -- pinning one obscure answer behind a chain of constraints -- while breadth, exhaustively enumerating a closed set and filling each item's attributes, is barely evaluated, especially outside English. Breadth is also hard to build: certifying that a gold set is complete…
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arxiv
Score 11.8
2026-06-29 · Ting-Wen Ko, Jonas Geiping
General AI
Large language models (LLMs) are increasingly used in open-ended multi-agent settings, but the long-run dynamics of model--model interaction remain poorly understood. We study whether open-ended LLM discussions exhibit attractor-like behavior, i.e. topic-independent stable sets of behaviors which conversations settle i…
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arxiv
Score 11.8
2026-06-29 · Yulin Zhou, Yimeng Wang, Nengyu Wang, Shaojia Xing, Shiyun Tu, Xiang Li, Jingkai Zhang, Ningbo Jiang, Yuankai Lin, Hua Yang, Xiangrui Zeng, Zhouping Yin
General AI
General-purpose robot policies should be modeled as dynamical systems, yet many VLA and generative imitation policies still rely on present observations or short windows. This Markovian shortcut fails in memory-dependent manipulation: identical observations can demand different actions after different histories. We pre…
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arxiv
Score 11.8
2026-06-29 · Iliana Fayolle, Sihem Bouhenniche, Samuel Pélissier, Pierre Laperdrix, Clémentine Maurice, Walter Rudametkin
Research Track B · General AI
Since 2023, a new class of bots has emerged: Web Agents. They can automate complex tasks on the Web, going beyond traditional browser automation tools such as Selenium, Puppeteer, or Playwright. Leveraging large language models (LLMs), these agents are capable of solving anti-bot mechanisms, mimicking human behavior, a…
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arxiv
Score 11.8
2026-06-29 · Mohit Raghavendra, Anisha Gunjal, Aakash Sabharwal, Yunzhong He
Research Track A · General AI
We introduce SWE-Interact, a new testbed for evaluating coding agents on multi-turn, interactive, user-driven software engineering tasks. Existing frontier SWE benchmarks typically provide complete requirements upfront and evaluate agents on autonomous implementation. In contrast, SWE-Interact places agents in a realis…
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arxiv
Score 11.8
2026-06-29 · Bryce Grant, Aryeh Rothenberg, Logan Senning, Zonghe Chua, Zach Patterson, Peng Wang
General AI
We present Sequential Planning via Anchored Robotic Keypoints, SPARK, a training-free neurosymbolic manipulation system that reaches 43.7% on six LIBERO-PRO position \& task cells, more than doubling CaP-Agent0 and Vision-Language-Action (VLA) baselines. CaP-Agent0, a multi-turn code-generation agent, achieves 18.2% by…
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arxiv
Score 11.5
2026-06-29 · Xinlei Yu, Gen Li, Qingyi Si, Guibin Zhang, Yuqi Xu, Congcong Wang, Shuai Dong, Kaiwen Tuo, Xiangyu Zeng, Kaituo Feng, Qunzhong Wang, Yang Shi, Xiaobin Hu, Xiangyu Yue, Jiaqi Wang, Shuicheng Yan
Research Track A · General AI
On-policy distillation (OPD) offers superior capacity transfer by supervising student-sampled trajectories with dense token-level signals. To furnish high-quality supervision sources and thereby elevate the performance frontier of distillation, an intuitive direction is to infuse privileged information to either teache…
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- unreviewed
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arxiv
Score 11.5
2026-06-29 · Yiting Hu, Lingjie Duan
Research Track A · General AI
Continual learning (CL), where a model is trained on a sequence of data tasks, is increasingly being adopted across key fields such as large language models and image recognition, yet it remains highly vulnerable to data poisoning that triggers learning divergence or severe excess risk. Despite these threats, a princip…
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huggingface
Score 11.4
2026-06-23 · Bingxuan Li, Yining Hong, Cheng Qian, Hyeonjeong Ha, Jiateng Liu, Zhenhailong Wang, Yue Guo, Yunzhu Li, Heng Ji
General AI
Physical interactions follow a long-tailed distribution: a set of common and regular interactions dominates human experience and visual data, while a broad spectrum of rare and irregular interactions remains underrepresented. Although recent visual world models, including image and video generation models, achieve impr…
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huggingface
Score 11.4
2026-06-24 · Simon Kurgan, Evan Wang, Eric Leonen, Sophie Szeto, Luke Alexander, Artemii Remizov, Jarod Alper, Giovanni Inchiostro, Vasily Ilin
General AI
Mathematical knowledge is organized around statements and their dependencies, but this structure is exposed unevenly: informal papers cite mostly at the document level, while formal libraries record fine-grained dependencies over a much smaller body of mathematics. We introduce TheoremGraph, a unified statement-level d…
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- pending
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- unreviewed
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- now
huggingface
Score 11.0
2026-06-28 · Ze Huang, Jiahui Zhang, Hairuo Liu, Chenxi Zhang, Ran Cheng, Li Zhang
General AI
We study action-conditioned world modeling as a scalable way to learn transferable dynamics priors for robot learning. By pretraining a model to predict how actions drive visual scene evolution, the resulting world model captures reusable interaction dynamics beyond appearance-level video generation. Concretely, we pre…
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huggingface
Score 11.0
2026-06-29 · Zhiqi Li, Chengrui Dong, Zhenhua Du, Hangning Zhou, Cong Qiu, Hailong Qin, Mu Yang, Dongxu Wei, Peidong Liu
General AI
Interactive video generation systems for camera-controlled world exploration roll out growing sequences of latent video frames, entangling state transition with high-frequency observation synthesis. We propose Walking in the Implicit, a scene-centric paradigm that changes the rollout variable from frame latents to a fi…
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- pending
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- unreviewed
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arxiv
Score 10.8
2026-06-29 · Haitao Wu, Qirui Zhang, Zhouheng Yao, Shangquan Sun, Qihao Zheng, Mianxin Liu, Chi Zhang, Wanli Ouyang, Chunfeng Song, Changqing Zhang, Jiamin Wu
General AI
Modeling the bidirectional correspondence between external sensory stimuli and internal neural activity has emerged as a critical frontier in neuroscience. However, existing approaches predominantly treat brain encoding and decoding as isolated tasks, relying heavily on unimodal alignment and external priors while over…
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arxiv
Score 10.8
2026-06-29 · Shun Lei, Huaicheng Zhang, Dapeng Wu, Yaoxun Xu, Lishi Zuo, Wei Tan, Hangting Chen, Guangzheng Li, Jianwei Yu, Zhiyong Wu, Dong Yu
General AI
Full-length song generation must preserve coherence and musicality, render detailed vocal and accompaniment acoustics, and follow lyrics and prompts. Existing language model-based systems face a structural trade-off: mixed-token modeling preserves vocal-instrument coordination but obscures track-specific details, where…
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arxiv
Score 10.8
2026-06-29 · Chuyue Li, Ziqi Tang, Jingyi Wang, Yu Wu, Kazuma Hashimoto, Lingyu Gao
General AI
With the advancement of Large Language Models (LLMs), code error detection has extended beyond traditional IDE diagnostics to context-sensitive debugging in educational scenarios. However, existing approaches lack large-scale datasets, multi-error analysis, and unified error taxonomies. To address this, we introduce Py…
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arxiv
Score 10.8
2026-06-29 · Mohamed el amine boudjoghra, Ivan Laptev, Angela Dai
General AI
Articulated 3D objects are essential for interactive environments in embodied AI, robotics, and virtual reality, but reconstructing their structure and motion from sparse observations remains challenging. Existing approaches remain largely constrained by lack of supervised data or lack the priors needed to reliably rec…
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- pending
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- unreviewed
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huggingface
Score 10.4
2026-06-25 · Xinyu Wang, Chongbo Zhao, Fangneng Zhan, Yue Ma
General AI
Streaming video editing has made rapid progress, yet practical deployment is still limited by two core issues: maintaining stable backgrounds and non-edited regions over time, and achieving the low latency required for real-time interactive scenarios. Meanwhile, recent streaming video generation methods are mostly deve…
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- pending
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- unreviewed
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huggingface
Score 10.4
2026-06-26 · Siqiao Xue, Chunxue Xu
General AI
Adapting a foundation vision-language encoder to a specialized retrieval task creates a fundamental tradeoff: gains on the target distribution come at the cost of the foundation model's broad generalization, and fashion retrieval is a stringent instance of this problem. We present ZooClaw-FashionSigLIP2, a fashion-spec…
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- pending
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- unreviewed
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huggingface
Score 10.0
2026-06-29 · Daniyel Ayupov, Artur Markov-Tsoy
General AI
We present DreamForge-World 0.1 Preview, a preview foundational world model for real-time interactive world simulation. The system adapts the LongLive 1 autoregressive video stack, itself derived from Wan2.1-T2V-1.3B, with a residual action pathway inspired by the Matrix-Game family. DreamForge-World 0.1 Preview focuse…
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- pending
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- unreviewed
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huggingface
Score 10.0
2026-06-29 · Yuxi Wang, Chengkai Jin, Yufei Liu, Wenqi Ouyang, Tianyi Wei, Zhiwei Zeng, Siyuan Huang, Zhiqi Shen, Xingang Pan
General AI
4D hand motion reconstruction from egocentric video is bottlenecked by clear limitations of existing methods: image-based pipelines depend on a detector that fails under heavy occlusion, while video-based methods rely on temporal modules learned only from scarce hand-pose annotations, a narrow signal insufficient to mo…
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- unreviewed
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arxiv
Score 9.8
2026-06-29 · Nicola Borri, Yukun Liu, Aleh Tsyvinski
General AI
Using 380 trillion tokens of realized AI consumption across more than four hundred large language models from the licensed proprietary OpenRouter dataset covering approximately 2 percent of current global monthly AI token consumption, we analyze how AI affects firms, markets, and workers. Leveraging the unprecedented s…
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- unreviewed
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arxiv
Score 9.8
2026-06-29 · Haoran Jin, Xiting Wang, Shijie Ren, Hong Xie, Defu Lian
General AI
Sparse Autoencoders (SAEs) are widely used to interpret large language models by decomposing activations into sparse, human-understandable features, but scaling to large dictionaries exposes fundamental challenges. Systematic studies reveal pervasive feature splitting that fragments coherent concepts into non-atomic la…
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arxiv
Score 9.8
2026-06-29 · Taixi Chen, Nancy Guo
General AI
Large-scale multimodal models (LMMs) have achieved superior performance in visual recognition by synergizing information across diverse, massive-scale paired modalities. In real-world scenarios, however, missing-modality inputs are ubiquitous, causing models optimized for modality-complete data to exhibit precipitous p…
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- unreviewed
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arxiv
Score 9.8
2026-06-29 · Lei Bai, Zongsheng Cao, Yang Chen, Zhiyao Cui, Shangheng Du, Yue Fan, Shiyang Feng, Zijie Guo, Haonan He, Liang He, Xiaohan He, Shuyue Hu, Yusong Hu, Songtao Huang, Yichen Jiang, Hao Li, Xin Li, Dahua Lin, Weihao Lin, Fenghua Ling, Dongrui Liu, Zhuo Liu, Runmin Ma, Chunjiang Mu, Haoyang Peng, Tianshuo Peng, Jinxin Shi, Luohe Shi, Boyuan Sun, Zelin Tan, Shengji Tang, Qianyi Wang, Yiming Wu, Yi Xie, Xiangchao Yan, Jingqi Ye, Peng Ye, Fangchen Yu, Jiakang Yuan, Bihao Zhan, Bo Zhang, Chen Zhang, Shufei Zhang, Shuaiyu Zhang, Wenlong Zhang, Yiqun Zhang, Junpeng Zhao, Zhijie Zhong, Bowen Zhou, Yuhao Zhou
General AI
We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We investigate agent-horizon scaling from two perspectives: scaling long-horizon trajectories and scaling heterogeneous agent abilities. To support this goal, we build a long-ho…
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arxiv
Score 9.0
2026-06-29 · Tianyu Wang, Gourav Rattihalli, Aditya Dhakal, Longfei Shangguan, Dejan Milojicic
Research Track A
As LLM inference becomes a major cloud workload, its growing energy footprint makes cluster-wide energy optimization increasingly important. Serverless LLM serving helps platforms absorb traffic volatility by elastically sharing GPU resources across models, but this sharing also makes energy optimization difficult. Mul…
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arxiv
Score 8.8
2026-06-28 · Satish Narayana Srirama
General AI
Fog computing utilizes proximal computational resources for sensor data processing and actuation, and addresses the latency, network load, and privacy issues of cloud-centric Internet of Things. On the other hand, Large Language Models (LLMs) are a type of deep learning AI models, which are trained on enormous text dat…
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- unreviewed
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arxiv
Score 8.8
2026-06-29 · Huaijie Wang, Shusheng Xu, Yi Wu, Kaifeng Lyu
General AI
A key step toward artificial general intelligence is to train models that can perform multiple tasks. In this paper, we study how to build such models by first training separate RL experts for individual tasks and then consolidating them via distillation, as an alternative to directly training a single model on mixed t…
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- unreviewed
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arxiv
Score 8.8
2026-06-29 · Kunyang Li, Kyle Domico, Jonathan Gregory, Patrick McDaniel
General AI
Multi-agent systems (MAS) are increasingly used to automate complex, distributed workflows. However, their inter-agent communication channels introduce new attack surfaces that remain poorly understood and are difficult to defend against. In this paper, we address how defenders should prioritize limited security effort…
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- unreviewed
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arxiv
Score 8.8
2026-06-29 · Jameel Hassan, Yasiru Ranasinghe, Vishal Patel
General AI
3D Gaussian Splatting (3DGS) has emerged at the forefront of 3D scene reconstruction. Extending 3DGS with language-driven, open-vocabulary understanding has gained significant attention for real-world applications such as embodied AI. Recent methods achieve this by learning an instance feature attribute and assigning s…
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arxiv
Score 8.8
2026-06-29 · Ziwei Su, Junyu Ren, Victor Veitch
General AI
Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignoring embedding magnitudes. However, surprisingly, empirical studies reveal that despite this, these "discarded" norms seem to correlate with semantic properties such as con…
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arxiv
Score 8.8
2026-06-29 · Yihao Wang, Yuheng Ji, Mingyu Cao, Yanqing Shen, Runze Xiao, Huaihai Lyu, Senwei Xie, Euan Liu, Klara Tian, Tianfeng Long, Yichi Zhang, Zhengliang Cai, Ruike Chen, Jifan Zhao, Ruochuan Shi, Zihan Tang, Jing Lyu, Wenxing Tan, Ningbo Zhang, Yangtao Hu, Yuming Gao, Xiansheng Chen, Junkai Zhao, Congsheng Xu, Boan Zhu, Ziqi Wang, Yupu Feng, Qiongqiong Zhang, Yingli Zhao, Yulong Ao, Shaoxuan Xie, You Liu, Guocai Yao, Leiduo Zhang, Xiaodan Liu, Yunyan Zhang, Yance Jiao, Xinyan Yang, Jiaxing Wei, Xu Liu, Tengfei Pan, Shaokai Nie, Chunlei Men, Sen Cui, Xiaojie Jin, Hongyang Li, Jianlan Luo, Yao Mu, Yunchao Wei, Jun Yan, Hang Zhao, Xiaolong Zheng, Jiaming Li, Yonghua Lin, Tiejun Huang, Zhongyuan Wang, Pengwei Wang
General AI
We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals and exposes it through multimodal readout interfaces. Rather than optimizing isolated next-token, next-frame, or next-action prediction, we are centered on Next-State-P…
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arxiv
Score 8.8
2026-06-29 · Shanshan Wang, Derek F. Wong, Jingming Yao, Lidia S. Chao
General AI
Traditional automatic evaluation methods have been shown to be unsuitable for modern Chinese poetry because of the distinct nature of this literary genre. Human evaluation remains reliable, but is expensive and not applicable to large-scale data. In this paper, we propose Poller (Poetry LLM Evaluator), a novel method l…
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arxiv
Score 8.8
2026-06-29 · Seunghun Baek, Jihwan Park, Jaeyoon Sim, Hoseok Lee, Seungjoo Lee, Won Hwa Kim
General AI
Multimodal MRI is essential for accurate brain tumor segmentation. However, acquiring all modalities at inference is often challenging in practice, which causes intrinsic uncertainty due to unavoidable information loss. Without modeling this uncertainty, existing methods encode incomplete evidence into deterministic re…
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huggingface
Score 8.4
2026-06-25 · Fenghe Guo, Runjie Shen, Chenyang Sun, Junrui Zhang, Quanxi Zhan, Yongchun Wang, Junjie Zhang
General AI
Hydropower tunnel inspection is critical for infrastructure integrity yet remains inefficient and hazardous using manual methods. We propose FLISP (Fast LiDAR-IMU Synchronized Path Planner), a mapless planning framework for cooperative UGV-UAV inspection. Unlike traditional map-based paradigms, FLISP features three cor…
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arxiv
Score 7.8
2026-06-29 · Subramanyam Sahoo, Aman Chadha, Vinija Jain, Divya Chaudhary
General AI
Conservative offline training is widely advocated as a safe foundation for subsequent online adaptation: if a policy stays close to well-supported behaviour, the argument goes, it is less likely to exploit imperfections in a learned reward model. We challenge this intuition empirically and mechanistically. We train a Q…
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arxiv
Score 7.8
2026-06-29 · Seunghun Baek, Jihwan Park, Jaeyoon Sim, Minjae Jeong, Hoseok Lee, Won Hwa Kim
General AI
As real-world prediction systems often face missing modalities at inference, incomplete multimodal learning (IML) remains a practical challenge. While prior methods aim to learn representations robust to missing inputs, representations from incomplete modalities inevitably deviate from their full-modality counterparts …
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arxiv
Score 5.8
2026-06-28 · Zhibin Duan, Yuhong Wang, Jiahong Fu, Zongsheng Yue, Bo Chen, Zongben Xu
General AI
While Low-rank adaptation (LoRA) enables highly efficient fine-tuning by constraining task-specific updates to fixed low-rank subspaces, this rigid design limits representational flexibility and often results in overconfident predictions and miscalibrated uncertainty, especially in low-data regimes. Recent Bayesian LoR…
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arxiv
Score 5.8
2026-06-28 · Andrew Mack, Nina Panickssery, Alexander Matt Turner
General AI
We aim to discover diverse, generalizable perturbations of LLM internals that can surface hidden behavioral modes. Such perturbations could help reshape model behavior and systematically evaluate potential risks. We introduce Causal Perturbative Elicitation (CPE), an unsupervised method for discovering interpretable lo…
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arxiv
Score 5.8
2026-06-28 · Zhihong Liu, Zheng Li, Jiachun Jin, Siqi Kou, Yitao Jian, Fengpei Yu, Zhijie Deng
General AI
While text-guided image editing has made remarkable progress, it remains limited in structural portrait retouching. Textual descriptions struggle to convey fine-grained changes to facial features and body proportions. To address this gap, we introduce Exemplar-Based Portrait Photo Retouching, where the model is given a…
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arxiv
Score 5.8
2026-06-29 · Yen-Jen Wang, Jiaman Li, Sirui Chen, Takara E. Truong, Pei Xu, Pieter Abbeel, Rocky Duan, Koushil Sreenath, Angjoo Kanazawa, Carmelo Sferrazza, Guanya Shi, Karen Liu
General AI
Perception-based humanoid loco-manipulation requires connecting egocentric observations and task instructions to whole-body motion. Learning this mapping requires synchronized egocentric images, language commands, and robot-compatible kinematic trajectories, yet no existing data source provides this complete tuple at s…
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huggingface
Score 5.4
2026-06-25 · Lang Huang, Jinglue Xu, Luke Darlow
General AI
Time-series forecasting research has been moving steadily toward larger architectures, from specialized transformers to general-purpose foundation models, on the assumption that capacity is what unlocks accuracy. We take the opposite position: most of the gap can be closed at far lower cost by tuning preprocessing rath…
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