6 papers
A Closer Look into LLMs for Table Understanding
Jia Wang, Chuanyu Qin, Mingyu Zheng +3
Despite the success of Large Language Models (LLMs) in table understanding, their internal mechanisms remain unclear. In this paper, we conduct an empirical study on 16 LLMs, cover…
PodBench: A Comprehensive Benchmark for Instruction-Aware Audio-Oriented Podcast Script Generation
Chenning Xu, Mao Zheng, Mingyu Zheng +1
Podcast script generation requires LLMs to synthesize structured, context-grounded dialogue from diverse inputs, yet systematic evaluation resources for this task remain limited. T…
NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tables
Lanrui Wang, Mingyu Zheng, Hongyin Tang +5
Processing structured tabular data, particularly large and lengthy tables, constitutes a fundamental yet challenging task for large language models (LLMs). However, existing long-c…
Test-time Prompt Intervention
Chenxu Yang, Qingyi Si, Mz Dai +5
Test-time compute has led to remarkable success in the large language model (LLM) community, particularly for complex tasks, where longer chains of thought (CoTs) are generated to…
Weights-Rotated Preference Optimization for Large Language Models
Chenxu Yang, Ruipeng Jia, Mingyu Zheng +6
Despite the efficacy of Direct Preference Optimization (DPO) in aligning Large Language Models (LLMs), reward hacking remains a pivotal challenge. This issue emerges when LLMs exce…
TableDreamer: Progressive and Weakness-guided Data Synthesis from Scratch for Table Instruction Tuning
Mingyu Zheng, Zhifan Feng, Jia Wang +4
Despite the commendable progress of recent LLM-based data synthesis methods, they face two limitations in generating table instruction tuning data. First, they can not thoroughly e…