activity
20242026
collaborators

15 papers

cs.CV2026

HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models

Feng He, Zhenting Wang, Qifan Wang +4

Hallucinations in vision language models (VLMs) are commonly treated as semantic errors, yet they often arise from partial or ambiguous visual evidence. Prior work mainly focuses o…

cs.CL2026

SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing

Ruikang Zhao, Zhenting Wang, Han Gao +1

Reinforcement learning for diffusion large language models (dLLMs) has largely moved to trajectory-aware methods. The current state of the art, TraceRL, holds that random masking i…

cs.AI2026

Evidence Over Plans: Online Trajectory Verification for Skill Distillation

Yang Zhou, Zihan Dong, Zhenting Wang +7

Agent skills can remarkably improve task success rates by using human-written procedural documents, but their quality is difficult to assess without environment-grounded verificati…

cs.CV2026

UniVL: Unified Vision-Language Embedding for Spatially Grounded Contextual Image Generation

Jiayun Wang, Yu Wang, Weijie Gan +2

We introduce spatially grounded contextual image generation, a controllable image generation task that reframes the conditioning paradigm. Instead of supplying a reference image an…

cs.CL2026

MemGym: a Long-Horizon Memory Environment for LLM Agents

Wujiang Xu, Yu Wang, Kai Mei +8

Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of personalized information in multi-…

cs.CL2026

A Single Layer to Explain Them All:Understanding Massive Activations in Large Language Models

Zeru Shi, Zhenting Wang, Fan Yang +2

We investigate the origins of massive activations in large language models (LLMs) and identify a specific layer named the \textbf{Massive Emergence Layer (ME Layer)}, that is consi…