activity
20232026
most citedTableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT

10 citations · 11 across the 18 of their papers we have counts for

collaborators

22 papers

cs.LG2026

Frozen Cores Need Task Signal: Fisher-Whitened Cross-Covariance for Low-Resource LLM Adaptation

Wentao Ye, Zhanming Shen, Zhiqing Xiao +3

Parameter-efficient fine-tuning is usually framed as a question of how many parameters to update. Under a severe trainable-state budget, however, where those coefficients act is eq…

cs.CL2026

Reasoning Error from Known Fact: Step-Level Self-Consistency Group Relative Policy Optimization for LLM

Xiaomeng Hu, Jiaqi Hu, Hao Chen +4

With the rapid advancement of large language models (LLMs), modern systems not only possess strong foundational capabilities and extensive knowledge, but can also solve complex pro…

cs.AI2026

Semantically Similar, Logically Distinct: Diagnosing the Semantic-Answerability Gap in Table RAG

Jiaming Tian, Liyao Li, Wentao Ye +5

Tables are a critical knowledge source in retrieval-augmented generation (RAG), but a retrieved table may lack sufficient evidence to answer a query, a property we call answerabili…

cs.AI2026

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think

Zhanming Shen, Jintao Tong, Shaotian Yan +9

On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference solutions provides token-lev…

cs.CV2026

Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching

Hao Zhong, Muzhi Zhu, Shenyan Zeng +8

Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained perception, and occlusion reasoning, making it a challenging testbed for…

cs.LG2026

FLaG: Fine-Grained Latent Grouping for Hallucination Detection

Wentao Ye, Liyao Li, Zhiqing Xiao +6

Hallucinations in large language models (LLMs) arise from heterogeneous failure mechanisms, making reliable detection difficult for any single global uncertainty score. In this wor…