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Total papers: 4 Search mode: keyword Shortlist (0) RSS

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Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 100% High protocol signal Freshness: Hot Status: Ready
Demonstrations Llm As Judge General
  • LLM evaluations drive which models get deployed, what safety standards get adopted, which research conclusions get published, and how projections of AI's labor-market impact get made.
  • Using Chatbot Arena data, we show naive 95\% CI coverage drops as n grows while TEE-corrected coverage holds at 95\%, and TEE-guided pipelines restrict the benchmark gaming surface from 56 to 32 Elo (K=27), below the human-leaderboard…
Open paper
LLM-as-a-Judge for Time Series Explanations

Preetham Sivalingam, Murari Mandal, Saurabh Deshpande, Dhruv Kumar · Apr 2, 2026

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 100% Moderate protocol signal Freshness: Warm Status: Fallback
Llm As JudgeAutomatic Metrics General
  • Although modern models generate textual interpretations of numerical signals, existing evaluation methods are limited: reference based similarity metrics and consistency checking models require ground truth explanations, while traditional…
  • To support this, we construct a synthetic benchmark of 350 time series cases across seven query types, each paired with correct, partially correct, and incorrect explanations.
Open paper

Match reason: Matched by broad semantic/index fallback.

Score: 65% Moderate protocol signal Freshness: Hot Status: Fallback
Llm As JudgeAutomatic Metrics General
  • We evaluate on HotpotQA-RAG v3, a controlled multi-hop benchmark, under an artifact-aware protocol (shortcut baselines, counterfactual swaps, no-oracle checks, GPT-4o audits).
  • Calibrated SURE-RAG reaches 0.9075 Macro-F1 (0.8951 +/- 0.0069), substantially above DeBERTa mean-pooling (0.6516) and a GPT-4o judge (0.7284), while matching a strong but opaque concat cross-encoder (0.8888 +/- 0.0109) with full…
Open paper
Citations: 0

Match reason: Matched by broad semantic/index fallback.

Score: 55% Moderate protocol signal Freshness: Warm Status: Ready
Rubric Rating Llm As Judge Medicine
  • We introduce ThReadMed-QA, a benchmark of 2,437 fully-answered patient-physician conversation threads extracted from r/AskDocs, comprising 8,204 question-answer pairs across up to 9 turns.
  • We evaluate five state-of-the-art LLMs -- GPT-5, GPT-4o, Claude Haiku, Gemini 2.5 Flash, and Llama 3.3 70B -- on a stratified test split of 238 conversations (948 QA pairs) using a calibrated LLM-as-a-judge rubric grounded in physician…
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