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cs.CL2026
A Representation-Level Assessment of Bias Mitigation in Foundation Models
Svetoslav Nizhnichenkov, Rahul Nair, Elizabeth Daly +1
We investigate how successful bias mitigation reshapes the embedding space of encoder-only and decoder-only foundation models, offering an internal audit of model behaviour through…
cs.CL2025
Interpreting LLM-as-a-Judge Policies via Verifiable Global Explanations
Jasmina Gajcin, Erik Miehling, Rahul Nair +3
Using LLMs to evaluate text, that is, LLM-as-a-judge, is increasingly being used at scale to augment or even replace human annotations. As such, it is imperative that we understand…
cs.CL2024
Ranking Large Language Models without Ground Truth
Amit Dhurandhar, Rahul Nair, Moninder Singh +2
Evaluation and ranking of large language models (LLMs) has become an important problem with the proliferation of these models and their impact. Evaluation methods either require hu…