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20242026
most citedVideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models

4 citations · 10 across the 14 of their papers we have counts for

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9 papers · 1 filter

cs.AI2026

ClawForge: Generating Executable Interactive Benchmarks for Command-Line Agents

Yuxiang Lai, Peng Xia, Haonian Ji +8

Interactive agent benchmarks face a tension between scalable construction and realistic workflow evaluation. Hand-authored tasks are expensive to extend and revise, while static pr…

cs.LG2026

AudioMosaic: Contrastive Masked Audio Representation Learning

Hanxun Huang, Qizhou Wang, Xingjun Ma +3

Audio self-supervised learning (SSL) aims to learn general-purpose representations from large-scale unlabeled audio data. While recent advances have been driven mainly by generativ…

cs.LG2026

EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents

Jiaqi Liu, Xinyu Ye, Peng Xia +4

Long-term memory is essential for LLM agents that operate across multiple sessions, yet existing memory systems treat retrieval infrastructure as fixed: stored content evolves whil…

cs.CV2026

CAST: Modeling Visual State Transitions for Consistent Video Retrieval

Yanqing Liu, Yingcheng Liu, Fanghong Dong +3

As video content creation shifts toward long-form narratives, composing short clips into coherent storylines becomes increasingly important. However, prevailing retrieval formulati…

cs.AI2026

In-Context Reinforcement Learning for Tool Use in Large Language Models

Yaoqi Ye, Yiran Zhao, Keyu Duan +4

While large language models (LLMs) exhibit strong reasoning abilities, their performance on complex tasks is often constrained by the limitations of their internal knowledge. A com…

cs.LG2026

SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

Peng Xia, Jianwen Chen, Hanyang Wang +10

Large Language Model (LLM) agents have shown stunning results in complex tasks, yet they often operate in isolation, failing to learn from past experiences. Existing memory-based m…

cs.CV2026

ViT-5: Vision Transformers for The Mid-2020s

Feng Wang, Sucheng Ren, Tiezheng Zhang +4

This work presents a systematic investigation into modernizing Vision Transformer backbones by leveraging architectural advancements from the past five years. While preserving the…

cs.LG2026

Reliable and Responsible Foundation Models: A Comprehensive Survey

Xinyu Yang, Junlin Han, Rishi Bommasani +49

Foundation models, including Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Image Generative Models (i.e, Text-to-Image Models and Image-Editing Models), a…

cs.CV2026

Spiral RoPE: Rotate Your Rotary Positional Embeddings in the 2D Plane

Haoyu Liu, Sucheng Ren, Tingyu Zhu +5

Rotary Position Embedding (RoPE) is the de facto positional encoding in large language models due to its ability to encode relative positions and support length extrapolation. When…