7 papers
Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement Learning
Duygu Nur Yaldiz, Evangelia Spiliopoulou, Zheng Qi +3
Large language models (LLMs) are increasingly deployed in decision-making tasks, where not only accuracy but also reliable confidence estimates are essential. Well-calibrated confi…
Journey Before Destination: On the importance of Visual Faithfulness in Slow Thinking
Rheeya Uppaal, Phu Mon Htut, Min Bai +3
Reasoning-augmented vision language models (VLMs) generate explicit chains of thought that promise greater capability and transparency but also introduce new failure modes: models…
Cross-Modal Content Optimization for Steering Web Agent Preferences
Tanqiu Jiang, Min Bai, Nikolaos Pappas +2
Vision-language model (VLM)-based web agents increasingly power high-stakes selection tasks like content recommendation or product ranking by combining multimodal perception with p…
Towards Long Context Hallucination Detection
Siyi Liu, Kishaloy Halder, Zheng Qi +6
Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. However, they are prone to contextual hallucination, generating information that is eith…
Rethinking LLM Uncertainty: A Multi-Agent Approach to Estimating Black-Box Model Uncertainty
Yu Feng, Phu Mon Htut, Zheng Qi +7
Quantifying uncertainty in black-box LLMs is vital for reliable responses and scalable oversight. Existing methods, which gauge a model's uncertainty through evaluating self-consis…
Inference time LLM alignment in single and multidomain preference spectrum
Sadat Shahriar, Zheng Qi, Nikolaos Pappas +5
Aligning Large Language Models (LLM) to address subjectivity and nuanced preference levels requires adequate flexibility and control, which can be a resource-intensive and time-con…