6 citations · 8 across the 27 of their papers we have counts for
10 papers · 1 filter
LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning
Zhengjun Huang, Zhoujin Tian, Qintian Guo +5
Large Language Model (LLM) agents exhibit remarkable conversational and reasoning capabilities but remain constrained by limited context windows and the lack of persistent memory.…
Data-Aware Socratic Query Refinement in Database Systems
Ruiyuan Zhang, Chrysanthi Kosyfaki, Xiaofang Zhou
In this paper, we propose Data-Aware Socratic Guidance (DASG), a dialogue-based query enhancement framework that embeds \linebreak interactive clarification as a first-class operat…
Reading Between the Timelines: RAG for Answering Diachronic Questions
Kwun Hang Lau, Ruiyuan Zhang, Weijie Shi +2
While Retrieval-Augmented Generation (RAG) excels at injecting static, factual knowledge into Large Language Models (LLMs), it exhibits a critical deficit in handling longitudinal…
EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora
Fangyuan Zhang, Zhengjun Huang, Yingli Zhou +6
Graph-based Retrieval-Augmented Generation (Graph-RAG) enhances large language models (LLMs) by structuring retrieval over an external corpus. However, existing approaches typicall…
Semantic-guided Diverse Decoding for Large Language Model
Weijie Shi, Yue Cui, Yaguang Wu +7
Diverse decoding of large language models is crucial for applications requiring multiple semantically distinct responses, yet existing methods primarily achieve lexical rather than…
Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists
Yue Cui, Liuyi Yao, Shuchang Tao +4
Large language models (LLMs) have significantly advanced natural language processing, particularly through the integration of external tools and APIs. However, their effectiveness…
Efficient Leave-one-out Approximation in LLM Multi-agent Debate Based on Introspection
Yue Cui, Liuyi Yao, Zitao Li +3
Multi-agent systems based on large language models (LLMs) advance automatic task completion in various fields, where debate is a common cooperation form for agents to solve complic…
Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens
Xixian Yong, Xiao Zhou, Yingying Zhang +3
The recent rise of Large Reasoning Models (LRMs) has significantly improved multi-step reasoning performance, but often at the cost of generating excessively long reasoning chains.…
ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects
Jipeng Zhang, Haolin Yang, Kehao Miao +4
Recent text-to-SQL models have achieved strong performance, but their effectiveness remains largely confined to SQLite due to dataset limitations. However, real-world applications…
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training
Weijie Shi, Jipeng Zhang, Yaguang Wu +8
Large language models (LLMs) are commonly trained on multi-domain datasets, where domain sampling strategies significantly impact model performance due to varying domain importance…