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Lihu Chen

7 accepted papers

2025

Evaluating Uncertainty Quantification Methods in Argumentative Large Language Models

EMNLP 2025

Research in uncertainty quantification (UQ) for large language models (LLMs) is increasingly important towards guaranteeing the reliability of this groundbreaking technology. We explore the integration of LLM UQ methods in argumentative LLMs (ArgLLMs), an explainable LLM framework for decision-makin

Cited by 0SourcePDFScholar
2025

Identifying Query-Relevant Neurons in Large Language Models for Long-Form Texts

AAAI 2025technical

Large Language Models (LLMs) possess vast amounts of knowledge within their parameters, prompting research into methods for locating and editing this knowledge. Previous work has largely focused on locating entity-related (often single-token) facts in smaller models. However, several key questions r…

2024

Reconfidencing LLMs from the Grouping Loss Perspective

EMNLP 2024finding

Large Language Models (LLMs), such as GPT and LLaMA, are susceptible to generating hallucinated answers in a confident tone. While previous efforts to elicit and calibrate confidence scores have shown some success, they often overlook biases towards certain groups, such as specific nationalities. Ex…

Cited by 8SourcePDFScholar
2022

Imputing Out-of-Vocabulary Embeddings with LOVE Makes LanguageModels Robust with Little Cost

ACL 2022long

State-of-the-art NLP systems represent inputs with word embeddings, but these are brittle when faced with Out-of-Vocabulary (OOV) words. To address this issue, we follow the principle of mimick-like models to generate vectors for unseen words, by learning the behavior of pre-trained embeddings using…

2021

A Lightweight Neural Model for Biomedical Entity Linking

AAAI 2021technical

Biomedical entity linking aims to map biomedical mentions, such as diseases and drugs, to standard entities in a given knowledge base. The specific challenge in this context is that the same biomedical entity can have a wide range of names, including synonyms, morphological variations, and names wit…