activity
20192026
most citedSemi-Supervised Few-Shot Learning with Prototypical Random Walks

5 citations · 5 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CV2026

EgoOmniWorld: Unifying Egocentric Understanding via Ego-Action-World Interactions

Songruo Chen, Yuqian Fu, Yu Li +7

Egocentric video understanding spans diverse capabilities, modalities, and evaluation formats, yet these are often studied in isolation despite their tight coupling in real-world i…

cs.CV2026

EgoProbe: Benchmarking Long-Range and Exact Memory in Streaming Egocentric Videos

Haokai Pang, Yuqian Fu, Yifei Wang +4

Egocentric video provides a continuous first-person record of everyday activities, making it a natural foundation for wearable AI assistants. Unlike offline video understanding, st…

cs.CV2026

Esports World Model Dataset

Weiyu Ma, Zeyuan Gong, Xuhui Liu +5

Interactive world models must capture how multiple participants jointly change a shared environment while observing different parts of it. Competitive games make this challenge con…

cs.CV2026

ObjectStream: Latent Objects as Memory Anchors for Streaming Video Understanding

Mingkang Dong, Muxin Pu, Jie Li +8

Streaming video understanding requires models to continuously retain useful visual evidence before future questions are known. Existing approaches primarily manage the growing visu…

cs.AI2026

Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning

Wenxuan Zhang, Yuhui Wang, Donggang Jia +5

Large Vision-Language Models (VLMs) now act as agents in interactive environments, where success requires coherent reasoning and decision-making across turns. Although end-to-end t…

cs.LG2026

A Shared Valence Axis Across Modern LLMs and Human EEG: The Saturation Regularity

Yousef A. Radwan, Xuhui Liu, Kilichbek Haydarov +2

Large language models (LLMs) have emerged as powerful representation learners whose internal features increasingly align with human cognition. We study whether modern LLMs can serv…

cs.CL2026

Freshness-Aware Prioritized Experience Replay for LLM/VLM Reinforcement Learning

Weiyu Ma, Yongcheng Zeng, Yan Song +4

Reinforcement Learning (RL) has achieved impressive success in post-training Large Language Models (LLMs) and Vision-Language Models (VLMs), with on-policy algorithms such as PPO,…

cs.AI2026

dTRPO: Trajectory Reduction in Policy Optimization of Diffusion Large Language Models

Wenxuan Zhang, Lemeng Wu, Changsheng Zhao +11

Diffusion Large Language Models (dLLMs) introduce a new paradigm for language generation, which in turn presents new challenges for aligning them with human preferences. In this wo…

cs.CV2026

Small Vision-Language Models are Smart Compressors for Long Video Understanding

Junjie Fei, Jun Chen, Zechun Liu +13

Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets and exacerbate the lost-in-the…

cs.AI2025

EvoCurr: Self-evolving Curriculum with Behavior Code Generation for Complex Decision-making

Yang Cheng, Weiyu Ma, Zilai Wang +6

Complex decision-making often requires agents to progress through intermediate tasks rather than solve the final target directly. Existing LLM self-refinement methods typically ite…

cs.LG2019★ 5 cited

Semi-Supervised Few-Shot Learning with Prototypical Random Walks

Ahmed Ayyad, Yuchen Li, Nassir Navab +2

Recent progress has shown that few-shot learning can be improved with access to unlabelled data, known as semi-supervised few-shot learning(SS-FSL). We introduce an SS-FSL approach…