huggingface
Score 22.8
2026-07-02 · Xiangchen Cheng, Yunwei Jiang, Jianwen Sun, Zizhen Li, Chuanhao Li, Xiangcheng Cao, Yihao Liu, Fanrui Zhang, Li Jin, Kaipeng Zhang
General AI
Memory for a long-horizon LLM agent is a contract about what each future decision is allowed to see. The simplest contract appends past observations, tool calls, and reflections to every prompt, which makes prior context easy to access but also turns it into a jumbled mixture in which the effect of any single memory co…
- Review
- pending
- Role
- unreviewed
- Read
- now
huggingface
Score 22.4
2026-06-26 · Yiling Tao, Shihan Deng, Meiling Tao, Pengzhi Wei, Zhichao Hu, Zhihao Zhu
General AI
Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking tasks, requiring multi-step retrieval and reasoning to fulfill user goals. However, existing benchmarks often assume that user queries are complete and explicit, overlooking the fact that real-world search r…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 22.3
2026-07-02 · Qianyu Chen, Canran Xiao, Runxuan Tang
Research Track A · General AI
Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether old answers remain correct, leaving the stability of multimodal grounding largely unexamined. We study this overlooked failure mode and ask whether a continually adapted …
- Review
- pending
- Role
- unreviewed
- Read
- now
huggingface
Score 21.0
2026-06-30 · Junha Jung, Minbyul Jeong, Suhyeon Lim, Sungwook Jung, Jaehoon Yun, Taeyun Roh, Mujeen Sung, Jaewoo Kang
General AI
Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-training pipelines remain predominantly outcome-centric, relying on final answer correctness or sequence-level preferences. This suffers from sparse credit assignment, making it difficult to optimize the reas…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 20.6
2026-07-02 · Liyan Tang, Fangcong Yin, Greg Durrett
General AI
Large vision-language models can reason over multimodal inputs by generating textual chains of thought (CoT). A key capability exhibited in CoT reasoning is self-reflection: revisiting earlier decisions and correcting previous errors. However, existing LVLMs often fail to properly attend to visual inputs during reflect…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 19.6
2026-07-02 · Yanjun Zhao, Ruizhong Qiu, Tianxin Wei, Yuanchen Bei, Zhining Liu, Lingjie Chen, Ismini Lourentzou, Hanghang Tong, Jingrui He
General AI
Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Although recent LLMs support increasingly long context windows, they often fail to use relevant evidence that is already present in the input, revealing a gap between context…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 18.8
2026-07-02 · Meng Wang, Haohan Zhao, Wenzhuo Liu, Lu Yang, Geng Liu, Haiyang Guo, Guo-Sen Xie, Gaofeng Meng, Hongbin Liu, Fei Zhu
Research Track A · General AI
Continual post-training enables foundation models to acquire new knowledge while preserving existing capabilities. Recent work suggests that on-policy learning can mitigate forgetting, with on-policy self-distillation emerging as a particularly attractive approach. In this work, we revisit this optimistic view through …
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 17.8
2026-06-30 · Ruijia Zhang, Jiacheng Zhu, Hanqing Zhu, Laixi Shi
General AI
Low-rank adaptation (LoRA) and its variants enable parameter-efficient fine-tuning of large language models under the supervised fine-tuning (SFT) paradigm. However, their efficacy and behavior under Reinforcement learning with verifiable rewards (RLVR) are less well understood. In particular, two structurally initiali…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 17.6
2026-07-02 · Yunhe Li, Hao Shi, Wenhao Liu, Mengzhe Ruan, Hanxu Hou, Zhongxiang Dai, Shuang Qiu, Linqi Song
General AI
On-policy self-distillation (OPSD) has emerged as a practical method for training large language models (LLMs) to reason, where a single model acts as both the teacher and the student with different levels of information access. However, recent studies have found that the teacher's dense token-level supervision, condit…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 17.6
2026-07-02 · Cristian-Gabriel Florea, Stelian Spînu
General AI
Over 285 million people worldwide live with a visual impairment, for whom everyday tasks such as avoiding obstacles, locating personal belongings, recognizing familiar faces, or handling cash remain persistent obstacles to personal autonomy. Existing assistive applications are typically limited to recognizing predefine…
- Review
- pending
- Role
- unreviewed
- Read
- now
huggingface
Score 16.8
2026-07-02 · Yueqi Song, Lintang Sutawika, Jiarui Liu, Lindia Tjuatja, Jiayi Geng, Yunze Xiao, Daniel Lee, Aditya Bharat Soni, Vincent Lo, Xiang Yue, Graham Neubig
General AI
Evaluating LLM agents on benchmarks like SWE-Bench and GAIA can be expensive, time-consuming, and requires complex infrastructure. A single evaluation can cost thousands of dollars and take days to complete. In contrast, non-agentic LLM benchmarks that test individual capabilities (e.g., reasoning, code generation) are…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 16.6
2026-07-02 · Yuxuan Li, Lingxi Xie, Xinyue Huo, Jihao Qiu, Jiacheng Shao, Pengfei Chen, Jiannan Ge, Kaiwen Duan, Qi Tian
General AI
Long-form TV dramas present a formidable challenge for comprehensive video understanding, where deciphering complex storyline often relies on \textbf{speaker recognition}, the task of accurately attributing each spoken utterance to its respective character. In this paper, we advance this field through two primary contr…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 16.6
2026-07-02 · Song Tang, Shuming Hu, Xincheng Shuai, Henghui Ding, Yu-Gang Jiang
General AI
Existing referring segmentation models passively process static images captured from fixed perspectives, limiting their applicability in Embodied AI, where agents must perform active perception in the continuous 360$^\circ$ environments. To bridge this gap, we introduce a novel task: Active Panoramic Referring Segmenta…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 16.6
2026-07-02 · Caleb Ziems, William Held, Su Doga Karaca, David Grusky, Tatsunori Hashimoto, Diyi Yang
General AI
Large Language Model (LLM) social simulations are a promising research method, but they are not yet faithful enough to be adopted widely. In this work, we investigate whether the current scaling paradigm in language modeling is likely to close these gaps, or whether simulation fidelity is orthogonal to general capabili…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 15.8
2026-06-30 · Runyu Lu, Yubo Wu, Ethan Kou, Letian Fu, Wenli Xiao, Ajay Mandlekar, Yinzhen Xu, Guanya Shi, Ken Goldberg, Ang Chen, Mosharaf Chowdhury, Yuke Zhu, Linxi "Jim" Fan, Guanzhi Wang
Research Track A · General AI
Traditional robot programming is challenging: it requires orchestrating multimodal perception, managing physical contact dynamics, and handling diverse configurations and execution failures. We introduce ASPIRE (Agentic Skill Programming through Iterative Robot Exploration), a continual learning system that autonomousl…
- Review
- pending
- Role
- unreviewed
- Read
- now
huggingface
Score 15.8
2026-07-02 · Zhilin Wang, Han Song, Runzhe Zhan, Jusen Du, Jiacheng Chen, Tianle Li, Qingyu Yin, Yulun Wu, Zhennan Shen, Tong Zhu, Yanshu Li, Guanjie Chen, Derek F. Wong, Yafu Li, Yu Cheng, Yang Yang
General AI
Autonomous agents are increasingly expected to improve executable policies through feedback, yet existing evaluations often collapse this process into a final score or confound it with open-ended software-engineering progress. We introduce Autonomous Policy Evolution, a controlled evaluation setting in which a harness-…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 15.6
2026-07-01 · Jiatong Li, Samuel Yeh, Sharon Li
Research Track A · General AI
Recurrent memory agents extend LLMs to arbitrarily long contexts by iteratively consolidating input into a fixed-size memory window. Despite their scalability, these agents exhibit a well-documented reliability problem: end-to-end performance degrades systematically as context length grows. We diagnose this failure by …
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 15.6
2026-07-02 · Jingtao Xu, Zizhuo Lin, Jianwen Sun, Yi Yang, Yawei Luo
General AI
While Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in standard visual understanding, adapting them for active visual search in 360$^\circ$ panoramic environments exposes fundamental limitations. Specifically, standard MLLMs struggle to effectively model inherent panoramic properti…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 15.6
2026-07-02 · Junyi Wen, Ruiyan Zhuang, Yongjia Xu, Pengtu Li, Rui Zou, Hongyi Chen, Chingman Wan, Puxu Yang, Wuhui Chen, Yanlin Wang
General AI
Developing high-performance kernels for Neural Processing Units (NPUs) is a critical industry bottleneck, requiring developers to manually navigate implicit hardware constraints and strict memory hierarchies. While large language models offer immense automation potential, they fail catastrophically on NPUs due to a fun…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 15.6
2026-07-02 · Francesca Pistilli, Simone Alberto Peirone, Giuseppe Averta
General AI
Understanding human behavior while interacting with the surrounding world is crucial for many applications of embodied AI. First-person videos are particularly informative for this problem, as they well capture how activities reshape the scene over time. However, existing approaches often rely on implicit visual or lan…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 15.6
2026-07-02 · Dazhi Fu, Jiuding Yang, Yiwen Guo, Jicong Fan
General AI
Reliable reward and preference signals are critical for evaluating and optimizing large language models on open-ended tasks. Rubric-based judges offer a transparent way to decompose such judgments into explicit evaluation criteria, but existing annotation-free rubric generators typically rely on a single generic evalua…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 14.8
2026-06-30 · Prakhar Dixit, Tim Oates
Research Track A · General AI
We propose Intelligent Schema Memory (ISM), a self-evolving memory-augmented system that improves mathematical reasoning for a frozen LLM under continual learning with hard episodic resets. ISM maintains a compact, self-refined bank of strategy schemas learned from both successful and failed episodes, with symbolic too…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 14.8
2026-06-30 · Gaurab Baral, Aaditya Khanal, Yangyang Tao, Junxiu Zhou
General AI
This paper investigates knowledge distillation from a large reasoning model (DeepSeek-R1) to a compact student model (Qwen2.5-7B). Using historical problems from the John O'Bryan Mathematics Competition at Northern Kentucky University (2011-2025), we build a Chain-of-Thought (CoT) training corpus through a dual-agent f…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 14.6
2026-07-02 · Emmanuel George, Christopher Keefe, Peter Pak, Amir Barati Farimani
General AI
Parts manufactured with Fused Deposition Modeling (FDM) often require Design for Additive Manufacturing (DFAM) modifications to ensure printability, structural integrity, and reduced post-processing. Current slicers identify defects such as steep overhangs but are unable to modify the underlying geometry. This work pre…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 13.6
2026-07-01 · Amirreza Rouhi, Rajat Aggarwal, Parikshit Sakurikar, Anoop M. Namboodiri, Sashi P. Reddi
General AI
Foundation video diffusion models are increasingly viewed as world simulators for embodied agents, yet their pretraining on internet-scale generic video leaves them poorly aligned with real-world deployment domains. We study parameter-efficient adaptation of a pretrained foundation video world model to retail scenes: w…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 13.6
2026-07-02 · Qiaowei Miao, Kehan Li, Yawei Luo, Yi Yang
General AI
Generative diffusion models excel at synthesizing high-quality images, videos, and 3D content under multimodal control. However, arbitrary user-defined modality-to-4D (X-to-4D) generation remains challenging due to the high cost of constructing diverse datasets and the limited scalability of existing methods. This pape…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 13.6
2026-07-02 · Jiale Amber Wang, Kaiyuan Wang, Pengyu Nie
General AI
Software tests and code evolve together: a code change should be followed by new or updated tests that record the new software behavior. Yet existing test generation and update benchmarks often isolate the test from the code change, and rely on static metadata that does not verify whether a test is executable or semant…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 13.5
2026-06-30 · Julien Lefebvre, Stefan Duffner, Mathieu Lefort
Research Track A · General AI
Online Continual Self-Supervised Learning (OCSSL) aims to learn representations from a continuous stream of unlabeled data, without knowledge of task boundaries and under memory constraints. Existing methods rely either on replay buffers that exploit latent space structure, or on regularization alone. We present CLIMB …
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 13.3
2026-07-02 · Xue Qin, Simin Luan, Cong Yang, Zhijun Li
Research Track A · General AI
Long-running adaptive intelligent agents face a structural tension between knowledge consolidation and information integrity. Memory consolidation is conventionally treated as an agent-changing operation: a model is fine-tuned, a prompt rewritten, a policy distilled, or a reflection appended to the context that governs…
- Review
- pending
- Role
- unreviewed
- Read
- now
huggingface
Score 12.8
2026-07-02 · Rintaro Otsubo, Ryo Fujii, Reina Ishikawa, Taiki Kanaya, Kanta Sawafuji, Hiroki Kajita, Shigeki Sakai, Hideo Saito, Ryo Hachiuma
Research Track A · General AI
Vision-Language Models (VLMs) have demonstrated immense promise in Spatio-Temporal Video Grounding (STVG). However, current evaluation protocols are largely confined to zero-shot assessments on general, daily-life benchmarks. This creates a critical disconnect from real-world applications in specialized fields, where m…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 12.6
2026-07-02 · Jijie Zhang, Zhe Ren, Quan Zhang, Dandan Guo
General AI
Large language models (LLMs) exhibit remarkable reasoning capabilities, but their task-specific fine-tuning is notoriously plagued by overconfidence, severely hindering trustworthy deployment. We propose Data-Adaptive Lower-Rank Adaptation (DALorRA), a simple and effective variational Bayesian sparse framework that shi…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 12.6
2026-07-02 · Wentao Zhang, Liliana Hotsko, Woojeong Kim, Pengyu Nie, Stuart Shieber, Yuntian Deng
General AI
Many everyday programming tasks resist clean rule-based implementation, such as alerting on important log lines, repairing malformed JSON, or ranking search results by intent, and are increasingly outsourced to large language model APIs at the cost of locality, reproducibility, and price. We propose fuzzy-function prog…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 12.3
2026-07-01 · Yuting Zhang, Yanbei Liu, Zhitao Xiao, Lei Geng, Yanwei Pang, Xiao Wang
Research Track A · General AI
Self-supervised Continual Graph Learning (CGL) aims to successively learn from a graph sequence with different tasks without label supervision - a paradigm that has attracted widespread attention. Most existing self-supervised CGL methods rely on instance-level consistency objectives that enforce stability of individua…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 11.6
2026-07-02 · Xuehui Wang, Xuankun Yang, Wei Shen
General AI
Visual token pruning is a crucial strategy for accelerating VLMs by compressing redundant image patches, yet existing methods often fail to preserve critical cues under dense instructions and fine-grained queries. In this paper, we investigate this failure and identify two underlying bottlenecks: the widespread dispers…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 11.6
2026-07-02 · Juanwu Lu, Junyu Zhu, Ziran Wang
General AI
Realistic traffic simulation requires agents that imitate logged behavior and can also be steered along interpretable axes. Such controllability enables engineers to isolate variables, reproduce specific edge cases, and test autonomous systems without real-world risk. We introduce Controllable Neural Variational Agents…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 11.6
2026-07-02 · Zhuowei Chen, Xiang Lorraine Li
General AI
Post-training large language models (LLMs) without real-world interaction feedback or human-labeled supervision remains challenging, particularly in specialized domains where expert annotations are costly to obtain. Recent annotation-free self-evolution methods address this by using the model's own outputs as supervisi…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 11.6
2026-07-02 · Arman Ghaffarizadeh, Danyal Mohaddes, Aliakbar Izadkhah, Shahriar Noroozizadeh
General AI
LLM agents will increasingly act in socially structured settings where role, audience, and relational context can shape what is advantageous or costly to say. We study whether such social structure, without any explicit objective in the prompt, changes what an agent expresses publicly relative to an off-the-record (OTR…
- Review
- pending
- Role
- unreviewed
- Read
- now
arxiv
Score 11.1
2026-07-02 · Quoc Bao Phan, Tuy Tan Nguyen
General AI
Federated learning (FL) enables collaborative model training across distributed devices without sharing raw data, making it suitable for privacy-sensitive robotic sensing applications. However, multi-agent systems generate heterogeneous and non-independent and identically distributed (non-IID) multimodal sensor streams…
- Review
- pending
- Role
- unreviewed
- Read
- soon
huggingface
Score 11.0
2026-06-29 · Disen Lan, Jianbin Zheng, Yuxi Ren, Xin Xia, Xuanda Wang, Xuefeng Xiao, Xipeng Qiu, Yu Cheng
General AI
Hybrid attention models improve long-context efficiency by retaining only a subset of full-attention layers and replacing the remaining layers with linear attention. However, the effectiveness of Transformer-to-hybrid conversion critically depends on which layers preserve full attention. Existing hybrid layer selection…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 10.6
2026-07-02 · Josh Hills, Ida Caspary, Asa Cooper Stickland
General AI
As AI coding agents become more autonomous, they increasingly ship code iteratively, with the codebase persisting across sessions. This persistence creates a new attack surface: a misaligned or prompt-injected agent can distribute attacks across pull requests (PRs) and time its payload for the PR with the best natural …
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 10.6
2026-07-02 · Vivienne Ming
General AI
Whether pairing people with AI helps or hurts is usually reported as a single average effect. Using a real-money prediction market (Polymarket) as an objective, externally resolved benchmark, this pilot shows that the value of human-AI collaboration depends on a specific, measurable form of human capital. Analyzed at t…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 10.6
2026-07-02 · Matteo Boglioni, Thibault Rousset, Siva Reddy, Marius Mosbach, Verna Dankers
General AI
LLMs memorize sensitive training data, including personally identifiable information (PII), creating a pressing need for reliable post hoc removal methods. Unlearning has emerged as a promising solution, with state-of-the-art(SOTA) methods often following a localize-first, unlearn-second paradigm that targets specific …
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 10.5
2026-06-30 · Kaisen Yang, Zheng Jiang, Yuzhao Peng, Houde Qian, Boshi Zhang, Youjie Zheng, Shijin Hong, Qingle Liu, Ruoyu Han, Bohan Lyu, Bingxiang He, Eren Cai, Calvin Xiao, Qinhuai Na
Research Track A · Research Track B · General AI
Internet users collectively perform an enormous range of skilled work through web browsers, from software development and document editing to search, forms, and enterprise workflows, making human browsing a highly scalable but under-exploited source of reusable browser skills. We argue that the bottleneck for browser a…
- Review
- pending
- Role
- unreviewed
- Read
- soon
huggingface
Score 10.0
2026-06-27 · Yongjin Yang, Jiarui Liu, Yinghui He, Lechen Zhang, Bernhard Schölkopf, Zhijing Jin
General AI
Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematics, programming, and science. However, the training curriculum (how often each domain is sampled) is typically fixed or hand-tuned, even though reasoning skills transfer…
- Review
- pending
- Role
- unreviewed
- Read
- soon
huggingface
Score 9.8
2026-07-01 · Max Van Puyvelde, Halil Ibrahim Gulluk, Wim Van Criekinge, Olivier Gevaert
General AI
Diffusion language models, which generate text by denoising a token canvas bidirectionally instead of emitting tokens left to right, have become competitive with autoregressive (AR) generation. Medical foundation models, however, remain almost entirely autoregressive. We adapt a mixture-of-experts diffusion language mo…
- Review
- pending
- Role
- unreviewed
- Read
- soon
huggingface
Score 9.8
2026-07-02 · Jiayin Zhu, Kelong Mao, Yudong Guo, Dengbo He, Sulong Xu, Simiu Gu, Yutao Yue
General AI
Skills are becoming a reusable operational layer for LLM agents, encoding SOPs, domain rules, tool workflows, scripts, and validation routines. In realistic skill repositories, overlapping skills make reliable skill-use difficult. Final verifier success is too coarse for both evaluation and training, since an agent may…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 9.6
2026-07-01 · Ran Yan, Wei Fu, Jiale Li, Shusheng Xu, Zhiyu Mei, Jiaxuan Gao, Jiarui Zhang, Wentai Zhang, Hao Dai, Xujie Shen, Chuyi He, Zhen Pu, Jun Mei, Zhiyao Lin, Haitao Wang, Zhiqiang Ding, Jiawei Zhang, Huaijie Wang, Ruida Xu, Honghua Dong, Youhe Jiang, Yi Wu, Tongkai Yang, Binhang Yuan
General AI
LLM agents are rapidly being deployed in production, including coding assistants, customer-support chatbots, and scientific research assistants, yet they remain fundamentally static in enterprise deployment. The LLM weights, system prompts, tool repertoires, and in-context harnesses are frozen at deployment time, and a…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 9.6
2026-07-02 · Kent K. Chang
General AI
Language models are increasingly used to quantify cultural phenomena, but what makes such measurement distinctively cultural? This paper argues that NLP work on culture is a material-discursive practice: the apparatus -- model, data, annotation, evaluation -- participates in constituting the cultural reality it measure…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 9.6
2026-07-02 · Mona Schirmer, Metod Jazbec, Alexander Timans, Christian Naesseth, Maja Waldron, Eric Nalisnick
General AI
Despite alignment training, LLMs remain prone to generating unsafe outputs at deployment time. Monitoring outputs online and raising an alarm when safety can no longer be assumed is therefore critical. We study a simple real-time monitor that turns a verifier signal from an external model into an alarm decision by thre…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 8.6
2026-07-02 · Xi Zhang, Papi Menon, Vivian Chu, Koray Cosguner
General AI
Since ChatGPT's launch in November 2022, open-source agentic frameworks have proliferated, making framework selection important for engineering teams while obscured by popularity signals such as GitHub stars. This paper analyzes 15 major open-source AI agent framework repositories from late 2022 to early 2026, using 80…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 7.6
2026-07-02 · Timo Bertram, Sidhant Bhavnani, Richard Freinschlag, Erich Kobler, Andreas Mayr, Günter Klambauer
General AI
In this work, we focus on SE-RRMs, a symbol-equivariant instantiation of RRMs that exhibits improved extrapolation to larger problem sizes. We propose a neuro-symbolic approach, ``Guiding with Recurrent Reasoning Models'' (G-RRM), which integrates SE-RRMs with symbolic solvers for constraint satisfaction problems. SE-R…
- Review
- pending
- Role
- unreviewed
- Read
- soon
arxiv
Score 7.6
2026-07-02 · Federico Lincetto, Gianluca Agresti, Mattia Rossi, Piergiorgio Sartor, Pietro Zanuttigh
General AI
Neural rendering techniques allow for accurate reconstruction of the geometry and color appearance of 3D scenes. Some methods have extended their use to additional imaging modalities, such as multispectral, infrared, or polarimetric data. However, all of these approaches require expensive sensors and calibrated setups …
- Review
- pending
- Role
- unreviewed
- Read
- soon
huggingface
Score 6.8
2026-07-02 · Dengyang Jiang, Mengmeng Wang, Harry Yang, Jingdong Wang
General AI
Representation alignment has become an effective way to accelerate diffusion transformer training and improve generation quality. Recent self-alignment methods, such as SRA and Self-Flow, further remove the dependency on external pretrained encoders by constructing alignment within the diffusion model itself. However, …
- Review
- pending
- Role
- unreviewed
- Read
- later
huggingface
Score 6.8
2026-07-02 · Junhao Shi, Siyin Wang, Xiaopeng Yu, Li Ji, Jingjing Gong, Xipeng Qiu
General AI
Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions, and actions that are costly to collect at scale. We argue that this bottleneck stems from conflating two distinct learning objectives: acquiring physical competence (how…
- Review
- pending
- Role
- unreviewed
- Read
- later
huggingface
Score 6.8
2026-07-02 · Xingyu Zheng, Xianglong Liu, Yifu Ding, Weilun Feng, Junqing Lin, Jinyang Guo, Haotong Qin
General AI
Hardware-agnostic strategies for accelerating text-to-image diffusion, such as timestep distillation and feature caching, can reduce inference time without custom kernels or system-level optimization. Among them, multi-resolution generation strategies have recently received broad attention, attaining more than 5x speed…
- Review
- pending
- Role
- unreviewed
- Read
- later
arxiv
Score 6.6
2026-07-01 · Riley Acker, Aman Desai, Garrett Kenyon, Frank Barrows
General AI
Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation and represent information through phase relationships. Their interactions can be designed to support intrinsic energy-minimizing dynamics, enabling tasks such as associat…
- Review
- pending
- Role
- unreviewed
- Read
- later
arxiv
Score 6.6
2026-07-02 · Haofei Xu, Rundi Wu, Philipp Henzler, Nikolai Kalischek, Michael Oechsle, Fabian Manhardt, Marc Pollefeys, Andreas Geiger, Federico Tombari, Michael Niemeyer
General AI
State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage pre-trained latent diffusion models. In this work, we show that such architectural overhead and intricate loss formulations are unnecessary.…
- Review
- pending
- Role
- unreviewed
- Read
- later
arxiv
Score 6.6
2026-07-02 · Shahreen Salim, Klaus Mueller
General AI
Large language model personas are increasingly used to approximate diverse users during early-stage visualization design, but it remains unclear whether persona-conditioned outputs reflect stable personality effects or artifacts of model choice and task framing. We examine this question across two visualization-relevan…
- Review
- pending
- Role
- unreviewed
- Read
- later
arxiv
Score 6.6
2026-07-02 · Hanlin Wang, Hao Ouyang, Qiuyu Wang, Wen Wang, Qingyan Bai, Ka Leong Cheng, Yue Yu, Yixuan Li, Yihao Meng, Zichen Liu, Yanhong Zeng, Yujun Shen, Qifeng Chen
General AI
We present WorldDirector, a highly controllable video world model framework designed for persistent dynamic object memory and unrestricted viewpoint exploration. Unlike existing world models that entangle physical dynamics with pixel rendering and rely on continuous visual observation to sustain motion, our framework e…
- Review
- pending
- Role
- unreviewed
- Read
- later
arxiv
Score 5.8
2026-06-30 · Tom Saliencro, Maya Lindqvist, Rohan Desai, Priya Nair, Daniel Whitmore
General AI
Parameter-efficient fine-tuning (PEFT) reparameterizes weight updates in a fixed basis: low-rank adapters operate in the spatial domain, while a recent line of spectral methods operates in a fixed Fourier domain. We argue that the choice of domain is itself a design degree of freedom that should be learned, and that no…
- Review
- pending
- Role
- unreviewed
- Read
- later
arxiv
Score 5.8
2026-06-30 · Shuai Yuan, Sudong Cai, Bingzhi Chen, Shuyuan Zheng, Chuan Xiao, Makoto Onizuka, Rui Mao
General AI
Low-rank adaptation (LoRA) is commonly viewed as an update-space approximation to full fine-tuning, yet this view is incomplete for self-gated Transformer feed-forward networks. In gated FFNs, a low-rank residual can change not only projected features but also the nonlinear selection weights that determine which channe…
- Review
- pending
- Role
- unreviewed
- Read
- later