7 citations · 15 across the 28 of their papers we have counts for
7 papers · 1 filter
Bounds of Chain-of-Thought Robustness: Reasoning Steps, Embed Norms, and Beyond
Dingzirui Wang, Xuanliang Zhang, Keyan Xu +3
Existing research indicates that the output of Chain-of-Thought (CoT) is significantly affected by input perturbations. Although many methods aim to mitigate such impact by optimiz…
Multi-Layer Attention is the Amplifier of Demonstration Effectiveness
Dingzirui Wang, Xuangliang Zhang, Keyan Xu +3
Numerous studies have investigated the underlying mechanisms of in-context learning (ICL) effectiveness to inspire the design of related methods. However, existing work predominant…
Format-Adapter: Improving Reasoning Capability of LLMs by Adapting Suitable Format
Dingzirui Wang, Xuanliang Zhang, Rongyu Cao +8
Generating and voting multiple answers is an effective method to mitigate reasoning inconsistencies of large language models (LLMs). Prior works have shown that multiple reasoning…
AlignEvoSkill: Towards Knowledge-Aware and Task-Aligned Agent Skill Evolution
Dingzirui Wang, Xuanliang Zhang, Keyan Xu +3
Reusable skills play a key role in improving LLM-based agents, but existing skill-evolution methods often fail to ensure that evolved skills both cover the knowledge required by th…
RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals
Xuanliang Zhang, Dingzirui Wang, Keyan Xu +2
The table reasoning task, crucial for efficient data acquisition, aims to answer questions based on the given table. Recently, reasoning large language models (RLLMs) with Long Cha…
Abacus-SQL: A Text-to-SQL System Empowering Cross-Domain and Open-Domain Database Retrieval
Keyan Xu, Dingzirui Wang, Xuanliang Zhang +2
The existing text-to-SQL systems have made significant progress in SQL query generation, but they still face numerous challenges. Existing systems often lack retrieval capabilities…
MULTITAT: Benchmarking Multilingual Table-and-Text Question Answering
Xuanliang Zhang, Dingzirui Wang, Keyan Xu +2
Question answering on the hybrid context of tables and text (TATQA) is a critical task, with broad applications in data-intensive domains. However, existing TATQA datasets are limi…