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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.CL2026

Judge, Retrieve, or Abstain: Uncertainty-Guarded LLM Judging with Provable Risk Guarantees

Sher Badshah, Ali Emami, Hassan Sajjad

Using LLMs as judges has become standard practice for evaluating model outputs at scale. This is particularly common for subjective, open-ended tasks such as assessing helpfulness…

cs.CL2026

SCOPE: Selective Conformal Optimized Pairwise LLM Judging

Sher Badshah, Ali Emami, Hassan Sajjad

Large language models (LLMs) are increasingly used as scalable judges in pairwise evaluation, but they remain prone to miscalibration and biases. We propose \textsc{Scope} (Selecti…

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…

cs.CL2024★ 4 cited

Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form QA

Sher Badshah, Hassan Sajjad

The emergence of Large Language Models (LLMs) as chat assistants capable of generating human-like conversations has amplified the need for robust evaluation methods, particularly f…