7 citations · 13 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…
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…