6 citations · 23 across the 17 of their papers we have counts for
19 papers
EvolSQL: Structure-Aware Evolution for Scalable Text-to-SQL Data Synthesis
Xuanguang Pan, Chongyang Tao, Jiayuan Bai +5
Training effective Text-to-SQL models remains challenging due to the scarcity of high-quality, diverse, and structurally complex datasets. Existing methods either rely on limited h…
Learning to Evolve: Bayesian-Guided Continual Knowledge Graph Embedding
Linyu Li, Zhi Jin, Yuanpeng He +6
As social media and the World Wide Web become hubs for information dissemination, effectively organizing and understanding the vast amounts of dynamically evolving Web content is c…
Rethinking Generalization in Knowledge Graph Embedding: An Empirical Study and Sparse Peak Regularization
Linyu Li, Zhi Jin, Yuanpeng He +8
Knowledge graphs (KGs) provide structured representations of entities and relations, and underpin data management and Web applications such as search, recommendation, and question…
GraphCodeAgent: Dual Graph-Guided LLM Agent for Retrieval-Augmented Repo-Level Code Generation
Jia Li, Xianjie Shi, Kechi Zhang +10
Writing code requires significant time and effort in software development. To automate this process, researchers have made substantial progress for code generation. Recently, large…
PROPHET: An Inferable Future Forecasting Benchmark with Causal Intervened Likelihood Estimation
Zhengwei Tao, Pu Wu, Zhi Jin +8
Predicting future events based on news on the Web stands as one of the ultimate aspirations of artificial intelligence. Recent advances in large language model (LLM)-based systems…
Enhancing LLM Generation with Knowledge Hypergraph for Evidence-Based Medicine
Chengfeng Dou, Ying Zhang, Zhi Jin +4
Evidence-based medicine (EBM) plays a crucial role in the application of large language models (LLMs) in healthcare, as it provides reliable support for medical decision-making pro…
LONGCODEU: Benchmarking Long-Context Language Models on Long Code Understanding
Jia Li, Xuyuan Guo, Lei Li +7
Current advanced long-context language models offer great potential for real-world software engineering applications. However, progress in this critical domain remains hampered by…
Revisit Self-Debugging with Self-Generated Tests for Code Generation
Xiancai Chen, Zhengwei Tao, Kechi Zhang +7
Large language models (LLMs) have shown significant advancements in code generation, but still face challenges on tasks beyond their basic capabilities. Recently, the notion of sel…
LLMs are Also Effective Embedding Models: An In-depth Overview
Chongyang Tao, Tao Shen, Shen Gao +6
Large language models (LLMs) have revolutionized natural language processing by achieving state-of-the-art performance across various tasks. Recently, their effectiveness as embedd…
Exploring LLM-based Data Annotation Strategies for Medical Dialogue Preference Alignment
Chengfeng Dou, Ying Zhang, Zhi Jin +4
This research examines the use of Reinforcement Learning from AI Feedback (RLAIF) techniques to improve healthcare dialogue models, with the aim of tackling the challenges of prefe…
EVIT: Event-Oriented Instruction Tuning for Event Reasoning
Zhengwei Tao, Xiancai Chen, Zhi Jin +3
Events refer to specific occurrences, incidents, or happenings that take place under a particular background. Event reasoning aims to infer events according to certain relations an…
MEEL: Multi-Modal Event Evolution Learning
Zhengwei Tao, Zhi Jin, Junqiang Huang +5
Multi-modal Event Reasoning (MMER) endeavors to endow machines with the ability to comprehend intricate event relations across diverse data modalities. MMER is fundamental and unde…
A Comprehensive Evaluation on Event Reasoning of Large Language Models
Zhengwei Tao, Zhi Jin, Yifan Zhang +7
Event reasoning is a fundamental ability that underlies many applications. It requires event schema knowledge to perform global reasoning and needs to deal with the diversity of th…
A Survey on Self-Evolution of Large Language Models
Zhengwei Tao, Ting-En Lin, Xiancai Chen +7
Large language models (LLMs) have significantly advanced in various fields and intelligent agent applications. However, current LLMs that learn from human or external model supervi…
ODA: Observation-Driven Agent for integrating LLMs and Knowledge Graphs
Lei Sun, Zhengwei Tao, Youdi Li +1
The integration of Large Language Models (LLMs) and knowledge graphs (KGs) has achieved remarkable success in various natural language processing tasks. However, existing methodolo…
Integrating Physician Diagnostic Logic into Large Language Models: Preference Learning from Process Feedback
Chengfeng Dou, Zhi Jin, Wenpin Jiao +3
The use of large language models in medical dialogue generation has garnered significant attention, with a focus on improving response quality and fluency. While previous studies h…
Enhancing the Spatial Awareness Capability of Multi-Modal Large Language Model
Yongqiang Zhao, Zhenyu Li, Zhi Jin +6
The Multi-Modal Large Language Model (MLLM) refers to an extension of the Large Language Model (LLM) equipped with the capability to receive and infer multi-modal data. Spatial awa…
EvEval: A Comprehensive Evaluation of Event Semantics for Large Language Models
Zhengwei Tao, Zhi Jin, Xiaoying Bai +4
Events serve as fundamental units of occurrence within various contexts. The processing of event semantics in textual information forms the basis of numerous natural language proce…
PlugMed: Improving Specificity in Patient-Centered Medical Dialogue Generation using In-Context Learning
Chengfeng Dou, Zhi Jin, Wenping Jiao +3
The patient-centered medical dialogue systems strive to offer diagnostic interpretation services to users who are less knowledgeable about medical knowledge, through emphasizing th…