activity
20232026
most citedAssessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

14 citations · 28 across the 22 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

TableSeek: Structure-Preserving Agentic Evidence Seeking over Heterogeneous Table Corpora

Jiaming Tian, Liyao Li, Wentao Ye +5

Open-domain table retrieval seeks tables that contain sufficient evidence for answering a question or verifying a claim. Yet semantic relevance is often misleading: topically simil…

cs.AI2026

Semantically Similar, Yet Not Answerable: Diagnosing the Semantic-Answerability Gap in Table RAG

Jiaming Tian, Liyao Li, Wentao Ye +6

In retrieval-augmented generation (RAG), semantic relevance asks whether a source matches a query in meaning, while answerability asks whether it contains sufficient information to…

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.AI2025

Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligence

Jiaming Tian, Liyao Li, Wentao Ye +6

Tables are fundamental in domains such as finance, healthcare, and public administration, yet real-world table tasks often involve noise, structural heterogeneity, and semantic com…

cs.AI2023★ 10 cited

TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT

Liangyu Zha, Junlin Zhou, Liyao Li +22

Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate. The advancements in large language models (LLMs) have made…