54 citations · 83 across the 19 of their papers we have counts for
19 papers
TEXT2DB: Integration-Aware Information Extraction with Large Language Model Agents
Yizhu Jiao, Sha Li, Sizhe Zhou +2
The task of information extraction (IE) is to extract structured knowledge from text. However, it is often not straightforward to utilize IE output due to the mismatch between the…
Synergistic Weak-Strong Collaboration by Aligning Preferences
Yizhu Jiao, Xuchao Zhang, Zhaoyang Wang +7
Current Large Language Models (LLMs) excel in general reasoning yet struggle with specialized tasks requiring proprietary or domain-specific knowledge. Fine-tuning large models for…
Multimodal Search in Chemical Documents and Reactions
Ayush Kumar Shah, Abhisek Dey, Leo Luo +9
We present a multimodal search tool that facilitates retrieval of chemical reactions, molecular structures, and associated text from scientific literature. Queries may combine mole…
Schema-Guided Culture-Aware Complex Event Simulation with Multi-Agent Role-Play
Sha Li, Revanth Gangi Reddy, Khanh Duy Nguyen +7
Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society. Relying on historical events to project the f…
Temperature-Centric Investigation of Speculative Decoding with Knowledge Distillation
Siru Ouyang, Shuohang Wang, Minhao Jiang +4
Speculative decoding stands as a pivotal technique to expedite inference in autoregressive (large) language models. This method employs a smaller draft model to speculate a block o…
Law of the Weakest Link: Cross Capabilities of Large Language Models
Ming Zhong, Aston Zhang, Xuewei Wang +14
The development and evaluation of Large Language Models (LLMs) have largely focused on individual capabilities. However, this overlooks the intersection of multiple abilities acros…
RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph
Siru Ouyang, Wenhao Yu, Kaixin Ma +6
Large Language Models (LLMs) excel in code generation yet struggle with modern AI software engineering tasks. Unlike traditional function-level or file-level coding tasks, AI softw…
Investigating Instruction Tuning Large Language Models on Graphs
Kerui Zhu, Bo-Wei Huang, Bowen Jin +5
Inspired by the recent advancements of Large Language Models (LLMs) in NLP tasks, there's growing interest in applying LLMs to graph-related tasks. This study delves into the capab…
Establishing Knowledge Preference in Language Models
Sizhe Zhou, Sha Li, Yu Meng +3
Language models are known to encode a great amount of factual knowledge through pretraining. However, such knowledge might be insufficient to cater to user requests, requiring the…
Multi-LoRA Composition for Image Generation
Ming Zhong, Yelong Shen, Shuohang Wang +6
Low-Rank Adaptation (LoRA) is extensively utilized in text-to-image models for the accurate rendition of specific elements like distinct characters or unique styles in generated im…
Investigating Data Contamination for Pre-training Language Models
Minhao Jiang, Ken Ziyu Liu, Ming Zhong +4
Language models pre-trained on web-scale corpora demonstrate impressive capabilities on diverse downstream tasks. However, there is increasing concern whether such capabilities mig…
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction
Qingyun Wang, Zixuan Zhang, Hongxiang Li +4
Fine-grained few-shot entity extraction in the chemical domain faces two unique challenges. First, compared with entity extraction tasks in the general domain, sentences from chemi…
TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang +67
Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural language processing capabilities. Nonetheless, these LLMs prese…
RESIN-EDITOR: A Schema-guided Hierarchical Event Graph Visualizer and Editor
Khanh Duy Nguyen, Zixuan Zhang, Reece Suchocki +5
In this paper, we present RESIN-EDITOR, an interactive event graph visualizer and editor designed for analyzing complex events. Our RESIN-EDITOR system allows users to render and f…
Large Language Models on Graphs: A Comprehensive Survey
Bowen Jin, Gang Liu, Chi Han +3
Large language models (LLMs), such as GPT4 and LLaMA, are creating significant advancements in natural language processing, due to their strong text encoding/decoding ability and n…
Structured Chemistry Reasoning with Large Language Models
Siru Ouyang, Zhuosheng Zhang, Bing Yan +4
Large Language Models (LLMs) excel in diverse areas, yet struggle with complex scientific reasoning, especially in the field of chemistry. Different from the simple chemistry tasks…
Instruct and Extract: Instruction Tuning for On-Demand Information Extraction
Yizhu Jiao, Ming Zhong, Sha Li +4
Large language models with instruction-following capabilities open the door to a wider group of users. However, when it comes to information extraction - a classic task in natural…
The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions
Siru Ouyang, Shuohang Wang, Yang Liu +7
Recent progress in Large Language Models (LLMs) has produced models that exhibit remarkable performance across a variety of NLP tasks. However, it remains unclear whether the exist…
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
Ming Zhong, Chenxin An, Weizhu Chen +2
Large Language Models (LLMs) inherently encode a wealth of knowledge within their parameters through pre-training on extensive corpora. While prior research has delved into operati…