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20242026
most citedReference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form QA

4 citations · 6 across the 9 of their papers we have counts for

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cs.LG2025

Interpreting the Effects of Quantization on LLMs

Manpreet Singh, Hassan Sajjad

Quantization offers a practical solution to deploy LLMs in resource-constraint environments. However, its impact on internal representations remains understudied, raising questions…

cs.LG2025

Cross-Layer Discrete Concept Discovery for Interpreting Language Models

Ankur Garg, Xuemin Yu, Hassan Sajjad +1

Interpreting language models remains challenging due to the existence of residual stream, which linearly mixes and duplicates features across adjacent layers, causing single-layer…

cs.CL2025

SAGE: A Search-AuGmented Evaluation of Large Language Models on Free-Form QA

Sher Badshah, Ali Emami, Hassan Sajjad

As Large Language Models (LLMs) become increasingly used for question-answering (QA), relying on static, pre-annotated references for evaluation poses significant challenges in cos…

cs.CL2025

CLEV: LLM-Based Evaluation Through Lightweight Efficient Voting for Free-Form Question-Answering

Sher Badshah, Moamen Moustafa, Hassan Sajjad

Evaluating free-form Question Answering (QA) remains a challenge due to its diverse and open-ended nature. Traditional automatic metrics fail to capture semantic equivalence or acc…

cs.CL2025

Which Words Matter Most in Zero-Shot Prompts?

Nikta Gohari Sadr, Sangmitra Madhusudan, Hassan Sajjad +1

While zero-shot instructional prompts like "Let's think step-by-step" have revolutionized Large Language Model performance, a fundamental question remains unanswered: which specifi…