5 citations · 16 across the 22 of their papers we have counts for
23 papers
Self-Distillation with Verbal Regularization
Jiazheng Li, Yawei Li, Junru Lu +7
On-policy self-distillation (OPSD) trains a large language model using supervision from a teacher instantiated from the same model as the student. The teacher is conditioned on pri…
Towards Self-Improving Error Diagnosis in Multi-Agent Systems
Jiazheng Li, Emine Yilmaz, Bei Chen +1
Large Language Model (LLM)-based Multi-Agent Systems (MAS) enable complex problem-solving but introduce significant debugging challenges, characterized by long interaction traces,…
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
Zhenyi Shen, Junru Lu, Lin Gui +4
Sparse attention reduces the quadratic complexity of full self-attention but faces two challenges: (1) an attention gap, where applying sparse attention to full-attention-trained m…
LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop
Runcong Zhao, Artem Bobrov, Jiazheng Li +2
Effective feedback is essential for student learning but is time-intensive for teachers. We present LearnLens, a modular, LLM-based system that generates personalised, curriculum-a…
EnigmaToM: Improve LLMs' Theory-of-Mind Reasoning Capabilities with Neural Knowledge Base of Entity States
Hainiu Xu, Siya Qi, Jiazheng Li +4
Theory-of-Mind (ToM), the ability to infer others' perceptions and mental states, is fundamental to human interaction but remains challenging for Large Language Models (LLMs). Whil…
RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-Following
Junru Lu, Jiazheng Li, Guodong Shen +5
Role-playing is important for Large Language Models (LLMs) to follow diverse instructions while maintaining role identity and the role's pre-defined ability limits. Existing role-p…
Two Heads Are Better Than One: Dual-Model Verbal Reflection at Inference-Time
Jiazheng Li, Yuxiang Zhou, Junru Lu +4
Although preference optimization methods have improved reasoning performance in Large Language Models (LLMs), they often lack transparency regarding why one reasoning outcome is pr…
An Automated Explainable Educational Assessment System Built on LLMs
Jiazheng Li, Artem Bobrov, David West +2
In this demo, we present AERA Chat, an automated and explainable educational assessment system designed for interactive and visual evaluations of student responses. This system lev…
AERA Chat: An Interactive Platform for Automated Explainable Student Answer Assessment
Jiazheng Li, Artem Bobrov, Runcong Zhao +2
Explainability in automated student answer scoring systems is critical for building trust and enhancing usability among educators. Yet, generating high-quality assessment rationale…
ExDDI: Explaining Drug-Drug Interaction Predictions with Natural Language
Zhaoyue Sun, Jiazheng Li, Gabriele Pergola +1
Predicting unknown drug-drug interactions (DDIs) is crucial for improving medication safety. Previous efforts in DDI prediction have typically focused on binary classification or p…
Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoring
Jiazheng Li, Hainiu Xu, Zhaoyue Sun +4
Generating rationales that justify scoring decisions has been a promising way to facilitate explainability in automated scoring systems. However, existing methods do not match the…
Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence
Junru Lu, Jiazheng Li, Siyu An +4
Direct Preference Optimization (DPO) has emerged as a prominent algorithm for the direct and robust alignment of Large Language Models (LLMs) with human preferences, offering a mor…
Large Language Models Fall Short: Understanding Complex Relationships in Detective Narratives
Runcong Zhao, Qinglin Zhu, Hainiu Xu +4
Existing datasets for narrative understanding often fail to represent the complexity and uncertainty of relationships in real-life social scenarios. To address this gap, we introdu…
The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis
Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang +3
Understanding in-context learning (ICL) capability that enables large language models (LLMs) to excel in proficiency through demonstration examples is of utmost importance. This im…
NarrativePlay: Interactive Narrative Understanding
Runcong Zhao, Wenjia Zhang, Jiazheng Li +4
In this paper, we introduce NarrativePlay, a novel system that allows users to role-play a fictional character and interact with other characters in narratives such as novels in an…
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language Models
Jiazheng Li, Zhaoyue Sun, Bin Liang +2
Text classifiers built on Pre-trained Language Models (PLMs) have achieved remarkable progress in various tasks including sentiment analysis, natural language inference, and questi…
OverPrompt: Enhancing ChatGPT through Efficient In-Context Learning
Jiazheng Li, Runcong Zhao, Yongxin Yang +2
The remarkable performance of pre-trained large language models has revolutionised various natural language processing applications. Due to huge parametersizes and extensive runnin…
Distilling ChatGPT for Explainable Automated Student Answer Assessment
Jiazheng Li, Lin Gui, Yuxiang Zhou +3
Providing explainable and faithful feedback is crucial for automated student answer assessment. In this paper, we introduce a novel framework that explores using ChatGPT, a cutting…
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
Junru Lu, Jiazheng Li, Byron C. Wallace +2
Accessing medical literature is difficult for laypeople as the content is written for specialists and contains medical jargon. Automated text simplification methods offer a potenti…
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
Zhaoyue Sun, Jiazheng Li, Gabriele Pergola +5
The primary goal of drug safety researchers and regulators is to promptly identify adverse drug reactions. Doing so may in turn prevent or reduce the harm to patients and ultimatel…
NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-task Financial Forecasting
Linyi Yang, Jiazheng Li, Ruihai Dong +2
Financial forecasting has been an important and active area of machine learning research because of the challenges it presents and the potential rewards that even minor improvement…
AQP: An Open Modular Python Platform for Objective Speech and Audio Quality Metrics
Jack Geraghty, Jiazheng Li, Alessandro Ragano +1
Audio quality assessment has been widely researched in the signal processing area. Full-reference objective metrics (e.g., POLQA, ViSQOL) have been developed to estimate the audio…
Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis
Linyi Yang, Jiazheng Li, Pádraig Cunningham +3
While state-of-the-art NLP models have been achieving the excellent performance of a wide range of tasks in recent years, important questions are being raised about their robustnes…