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20242026
most citedHeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding

1 citations · 2 across the 12 of their papers we have counts for

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cs.AI2025

ELAIPBench: A Benchmark for Expert-Level Artificial Intelligence Paper Understanding

Xinbang Dai, Huikang Hu, Yongrui Chen +6

While large language models (LLMs) excel at many domain-specific tasks, their ability to deeply comprehend and reason about full-length academic papers remains underexplored. Exist…

cs.CL2025

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning

Yongrui Chen, Junhao He, Linbo Fu +10

Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and knowledge graphs in a unified way…

cs.LG2025

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models

Rihui Jin, Zheyu Xin, Xing Xie +6

Table reasoning (TR) requires structured reasoning over semi-structured tabular data and remains challenging, particularly for small language models (SLMs, e.g., LLaMA-8B) due to t…

cs.CL2025

After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation

Xinbang Dai, Huikang Hu, Yuncheng Hua +5

Retrieval-augmented generation (RAG) is a promising paradigm, yet its trustworthiness remains a critical concern. A major vulnerability arises prior to generation: models often fai…

cs.CL2025

Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge

Yongrui Chen, Junhao He, Linbo Fu +10

Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions (NLQs) by using structured sources such as tables, databases, and knowledge graphs in a unif…