40 citations · 100 across the 68 of their papers we have counts for
13 papers · 2 filters
QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
Dehai Min, Kailin Zhang, Tongtong Wu +1
Dynamic Retrieval-Augmented Generation adaptively determines when to retrieve during generation to mitigate hallucinations in large language models (LLMs). However, existing method…
Revisiting NLI: Towards Cost-Effective and Human-Aligned Metrics for Evaluating LLMs in Question Answering
Sai Shridhar Balamurali, Lu Cheng
Evaluating answers from state-of-the-art large language models (LLMs) is challenging: lexical metrics miss semantic nuances, whereas "LLM-as-Judge" scoring is computationally expen…
Early Risk Prediction with Temporally and Contextually Grounded Clinical Language Processing
Rochana Chaturvedi, Yue Zhou, Andrew D. Boyd +5
Clinical notes in Electronic Health Records (EHRs) capture rich temporal information on events, clinician reasoning, and lifestyle factors often missing from structured data. Lever…
A Lightweight Large Language Model-Based Multi-Agent System for 2D Frame Structural Analysis
Ziheng Geng, Jiachen Liu, Ran Cao +3
Large language models (LLMs) have recently been used to empower autonomous agents in engineering, significantly improving automation and efficiency in labor-intensive workflows. Ho…
SoM-1K: A Thousand-Problem Benchmark Dataset for Strength of Materials
Qixin Wan, Zilong Wang, Jingwen Zhou +5
Foundation models have shown remarkable capabilities in various domains, but their performance on complex, multimodal engineering problems remains largely unexplored. We introduce…
REHEARSE: Experiential Rehearsal for Verbal Confidence Calibration in Large Language Models
Ke Fang, Tianyi Zhao, Qianwen Wang +1
Large language models (LLMs) often express verbal confidence that is poorly aligned with actual correctness, limiting their reliability in safety-critical applications. Existing pr…
A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis
Jiachen Liu, Ziheng Geng, Ran Cao +3
Large language models (LLMs) have exhibited remarkable capabilities across diverse open-domain tasks, yet their application in specialized domains such as civil engineering remains…
CP-Router: An Uncertainty-Aware Router Between LLM and LRM
Jiayuan Su, Fulin Lin, Zhaopeng Feng +7
Recent advances in Large Reasoning Models (LRMs) have significantly improved long-chain reasoning capabilities over Large Language Models (LLMs). However, LRMs often produce unnece…
Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Models
Liangjie Huang, Dawei Li, Huan Liu +1
Large Language Models (LLMs) have demonstrated remarkable self-improvement capabilities, whereby models iteratively revise their outputs through self-generated feedback. While this…
Shakespearean Sparks: The Dance of Hallucination and Creativity in LLMs' Decoding Layers
Zicong He, Boxuan Zhang, Lu Cheng
Large language models (LLMs) are known to hallucinate, a phenomenon often linked to creativity. While previous research has primarily explored this connection through theoretical o…
DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models
Zihao Li, Ruixiang Tang, Lu Cheng +3
Pre-trained language models (PLMs) have achieved impressive results on various natural language processing tasks. However, recent research has revealed that these models often rely…
Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topology
Longchao Da, Xiaoou Liu, Jiaxin Dai +3
Understanding the uncertainty in large language model (LLM) explanations is important for evaluating their faithfulness and reasoning consistency, and thus provides insights into t…
COPU: Conformal Prediction for Uncertainty Quantification in Natural Language Generation
Sean Wang, Yicheng Jiang, Yuxin Tang +2
Uncertainty Quantification (UQ) for Natural Language Generation (NLG) is crucial for assessing the performance of Large Language Models (LLMs), as it reveals confidence in predicti…