1 citations · 1 across the 16 of their papers we have counts for
4 papers · 1 filter
Uncertainty as Feature Gaps: Epistemic Uncertainty Quantification of LLMs in Contextual Question-Answering
Yavuz Bakman, Sungmin Kang, Zhiqi Huang +8
Uncertainty Quantification (UQ) research has primarily focused on closed-book factual question answering (QA), while contextual QA remains unexplored, despite its importance in rea…
Confidence-Based Response Abstinence: Improving LLM Trustworthiness via Activation-Based Uncertainty Estimation
Zhiqi Huang, Vivek Datla, Chenyang Zhu +4
We propose a method for confidence estimation in retrieval-augmented generation (RAG) systems that aligns closely with the correctness of large language model (LLM) outputs. Confid…
Improving Consistency in Retrieval-Augmented Systems with Group Similarity Rewards
Faisal Hamman, Chenyang Zhu, Anoop Kumar +4
RAG systems are increasingly deployed in high-stakes domains where users expect outputs to be consistent across semantically equivalent queries. However, existing systems often exh…
RAFFLES: Reasoning-based Attribution of Faults for LLM Systems
Chenyang Zhu, Spencer Hong, Jingyu Wu +6
The advent of complex, interconnected long-horizon LLM systems has made it incredibly tricky to identify where and when these systems break down. Evaluation capabilities that curre…