ICLR 2025PastLarge language models

ICLR Workshop: Quantify Uncertainty and Hallucination in Foundation Models: The Next Frontier in Reliable AI

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Submission deadline: Feb 6, 2025, 11:59 UTC
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Accepted papers (37)

Fetched from OpenReview (v2) on 2026-06-10.

[TINY] Building Bridges of Thought: Using the Power of Association to Inspire Creativity in Large Language Models
Fang-Yi Su, Ching Chieh Tsao, Jung-Hsien Chiang · PDF
[TINY] Vision language models can implicitly quantify aleatoric uncertainty
Xi Wang, Eric Nalisnick · PDF
Adaptive Elicitation of Latent Information Using Natural Language
Jimmy Wang, Thomas P Zollo, Richard Zemel, Hongseok Namkoong · PDF
Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation
Mykyta Ielanskyi, Kajetan Schweighofer, Lukas Aichberger, Sepp Hochreiter · PDF
Assessing Confidence in Large Language Models by Classifying Task Correctness using Similarity Features
Debarun Bhattacharjya, Balaji Ganesan, Junkyu Lee, Radu Marinescu · PDF
Can Your Uncertainty Scores Detect Hallucinated Entity?
Min-Hsuan Yeh, Max Kamachee, Seongheon Park, Yixuan Li · PDF
Conformal Structured Prediction
Botong Zhang, Shuo Li, Osbert Bastani · PDF
Detecting Unreliable Responses in Generative Vision-Language Models via Visual Uncertainty
Kiana Avestimehr, Emily Aye, Zalan Fabian, Erum Mushtaq · PDF
FastRM: An efficient and automatic explainability framework for multimodal generative models
Gabriela Ben-Melech Stan, Estelle Aflalo, Man Luo, Shachar Rosenman, Tiep Le, Sayak Paul, Shao-Yen Tseng, Vasudev Lal · PDF
Finetuning Language Models to Emit Linguistic Expressions of Uncertainty
Arslan Chaudhry, Sridhar Thiagarajan, Dilan Gorur · PDF
Generative Uncertainty in Diffusion Models
Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric Nalisnick, Stephan Mandt · PDF
How to Steer LLM Latents for Hallucination Detection?
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh, Haobo Wang, Yixuan Li · PDF
Hybrid Preference Optimization for Alignment: Provably Faster Convergence Rates by Combining Offline Preferences with Online Exploration
Avinandan Bose, Zhihan Xiong, Aadirupa Saha, Simon Shaolei Du, Maryam Fazel · PDF
Learning on LLM Output Signatures for Gray Box LLM Behavior Analysis
Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron · PDF
LongProLIP: A Probabilistic Vision-Language Model with Long Context Text
Sanghyuk Chun, Sangdoo Yun · PDF
Monte Carlo Temperature: a robust sampling strategy for LLM's uncertainty quantification methods
Nicola Cecere, Andrea Bacciu, Ignacio Fernández-Tobías, Amin Mantrach · PDF
On Verbalized Confidence Scores for LLMs
Daniel Yang, Yao-Hung Hubert Tsai, Makoto Yamada · PDF
Predictive Inference Is Really Free with In-Context Learning
Sohom Mukherjee, Ivane Antonov, Kai Günder, Magnus Josef Maichle · PDF
Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolo Dalmasso, Natraj Raman, Sumitra Ganesh · PDF
Rethinking Uncertainty Estimation in Natural Language Generation
Lukas Aichberger, Kajetan Schweighofer, Sepp Hochreiter · PDF
Sample-Focused Approach for Robust Uncertainty Quantification in LLMs
Roman Vashurin, Maiya Goloburda, Preslav Nakov, Artem Shelmanov, Maxim Panov · PDF
Scalable Thompson Sampling via Ensemble++
Yingru Li, Jiawei Xu, Baoxiang Wang, Zhi-Quan Luo · PDF
Semantic-Level Confidence Calibration of Language Models via Temperature Scaling
Tom A. Lamb, Desi R. Ivanova, Philip Torr, Tim G. J. Rudner · PDF
TINY: Rethinking Selection Bias in LLMs: Quantification and Mitigation using Efficient Majority Voting
Blessed Guda, Lawrence Francis, Gabrial Zencha Ashungafac, Carlee Joe-Wong, Moise Busogi · PDF
TINY: Semantic-based Uncertainty Quantification in LLMS: A Case Study on Medical Explanation Generation Task.
Nicholas Kian Boon Tan, Mehul Motani · PDF
To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation
Kaustubh Dhole · PDF
Toward Trustworthy Neural Program Synthesis
Wen-Ding Li, Darren Yan Key, Kevin Ellis · PDF
Towards Lighter and Robust Evaluation for Retrieval Augmented Generation
Alex-Răzvan Ispas, Charles-Elie Simon, Fabien Caspani, Vincent Guigue · PDF
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang · PDF
Uncertainty of Vision Medical Foundation Models
Haoxu Huang, Narges Razavian · PDF
Uncertainty Quantification for MLLMs
Gregory Kang Ruey Lau, Hieu Dao, Bryan Kian Hsiang Low · PDF
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles
Oleksandr Balabanov, Hampus Linander · PDF
Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models
Omer Belhasin, Idan Kligvasser, George Leifman, Regev Cohen, Erin Rainaldi, Li-Fang Cheng, Nishant Verma, Paul Varghese, Ehud Rivlin, Michael Elad · PDF
Uncertainty-Aware Step-wise Verification with Generative Reward Models
Zihuiwen Ye, Luckeciano Carvalho Melo, Younesse Kaddar, Phil Blunsom, Sam Staton, Yarin Gal · PDF
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li · PDF
Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models
Ze Yu Zhang, Arun Verma, Finale Doshi-Velez, Bryan Kian Hsiang Low · PDF
Understanding the Sources of Uncertainty for Large Language and Multimodal Models
Ziran Yang, Shibo Hao, Hao Sun, Lai Jiang, Qiyue Gao, Yian Ma, Zhiting Hu · PDF

Accepted papers (37)

☆[TINY] Building Bridges of Thought: Using the Power of Association to Inspire Creativity in Large Language Models

☆[TINY] Vision language models can implicitly quantify aleatoric uncertainty

☆Adaptive Elicitation of Latent Information Using Natural Language

☆Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation

☆Assessing Confidence in Large Language Models by Classifying Task Correctness using Similarity Features

☆Can Your Uncertainty Scores Detect Hallucinated Entity?

☆Conformal Structured Prediction

☆Detecting Unreliable Responses in Generative Vision-Language Models via Visual Uncertainty

☆FastRM: An efficient and automatic explainability framework for multimodal generative models

☆Finetuning Language Models to Emit Linguistic Expressions of Uncertainty

☆Generative Uncertainty in Diffusion Models

☆How to Steer LLM Latents for Hallucination Detection?

☆Hybrid Preference Optimization for Alignment: Provably Faster Convergence Rates by Combining Offline Preferences with Online Exploration

☆Learning on LLM Output Signatures for Gray Box LLM Behavior Analysis

☆LongProLIP: A Probabilistic Vision-Language Model with Long Context Text

☆Monte Carlo Temperature: a robust sampling strategy for LLM's uncertainty quantification methods

☆On Verbalized Confidence Scores for LLMs

☆Predictive Inference Is Really Free with In-Context Learning

☆Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction

☆Rethinking Uncertainty Estimation in Natural Language Generation

☆Sample-Focused Approach for Robust Uncertainty Quantification in LLMs

☆Scalable Thompson Sampling via Ensemble++

☆Semantic-Level Confidence Calibration of Language Models via Temperature Scaling

☆TINY: Rethinking Selection Bias in LLMs: Quantification and Mitigation using Efficient Majority Voting

☆TINY: Semantic-based Uncertainty Quantification in LLMS: A Case Study on Medical Explanation Generation Task.

☆To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation

☆Toward Trustworthy Neural Program Synthesis

☆Towards Lighter and Robust Evaluation for Retrieval Augmented Generation

☆Training-Free Bayesianization for Low-Rank Adapters of Large Language Models

☆Uncertainty of Vision Medical Foundation Models

☆Uncertainty Quantification for MLLMs

☆Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

☆Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models

☆Uncertainty-Aware Step-wise Verification with Generative Reward Models

☆Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

☆Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models

☆Understanding the Sources of Uncertainty for Large Language and Multimodal Models

[TINY] Building Bridges of Thought: Using the Power of Association to Inspire Creativity in Large Language Models

[TINY] Vision language models can implicitly quantify aleatoric uncertainty

Adaptive Elicitation of Latent Information Using Natural Language

Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation

Assessing Confidence in Large Language Models by Classifying Task Correctness using Similarity Features

Can Your Uncertainty Scores Detect Hallucinated Entity?

Conformal Structured Prediction

Detecting Unreliable Responses in Generative Vision-Language Models via Visual Uncertainty

FastRM: An efficient and automatic explainability framework for multimodal generative models

Finetuning Language Models to Emit Linguistic Expressions of Uncertainty

Generative Uncertainty in Diffusion Models

How to Steer LLM Latents for Hallucination Detection?

Hybrid Preference Optimization for Alignment: Provably Faster Convergence Rates by Combining Offline Preferences with Online Exploration

Learning on LLM Output Signatures for Gray Box LLM Behavior Analysis

LongProLIP: A Probabilistic Vision-Language Model with Long Context Text

Monte Carlo Temperature: a robust sampling strategy for LLM's uncertainty quantification methods

On Verbalized Confidence Scores for LLMs

Predictive Inference Is Really Free with In-Context Learning

Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction

Rethinking Uncertainty Estimation in Natural Language Generation

Sample-Focused Approach for Robust Uncertainty Quantification in LLMs

Scalable Thompson Sampling via Ensemble++

Semantic-Level Confidence Calibration of Language Models via Temperature Scaling

TINY: Rethinking Selection Bias in LLMs: Quantification and Mitigation using Efficient Majority Voting

TINY: Semantic-based Uncertainty Quantification in LLMS: A Case Study on Medical Explanation Generation Task.

To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation

Toward Trustworthy Neural Program Synthesis

Towards Lighter and Robust Evaluation for Retrieval Augmented Generation

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models

Uncertainty of Vision Medical Foundation Models

Uncertainty Quantification for MLLMs

Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models

Uncertainty-Aware Step-wise Verification with Generative Reward Models

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models

Understanding the Sources of Uncertainty for Large Language and Multimodal Models