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Human Feedback and Eval Paper Explorer

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Total papers: 5 Search mode: keyword Shortlist (0) RSS

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RuleForge: Automated Generation and Validation for Web Vulnerability Detection at Scale

Ayush Garg, Sophia Hager, Jacob Montiel, Aditya Tiwari, Michael Gentile, Zach Reavis · Apr 2, 2026

Citations: 0

Match reason: Matches selected tags (Math, Expert Verification).

Score: 65% Moderate protocol signal Freshness: Hot Status: Ready
Expert Verification Llm As JudgeAutomatic Metrics Math
  • This paper focuses on RuleForge's architecture and operational deployment for CVE-related threat detection, with particular emphasis on our novel LLM-as-a-judge (Large Language Model as judge) confidence validation system and systematic…
  • We also present extensions enabling rule generation from unstructured data sources and demonstrate a proof-of-concept agentic workflow for multi-event-type detection.
Open paper
Generating and Evaluating Sustainable Procurement Criteria for the Swiss Public Sector using In-Context Prompting with Large Language Models

Yingqiang Gao, Veton Matoshi, Luca Rolshoven, Tilia Ellendorff, Judith Binder, Jeremy Austin Jann · Mar 23, 2026

Citations: 0

Match reason: Matches selected tags (Math, Expert Verification).

Score: 55% Moderate protocol signal Freshness: Warm Status: Fallback
Expert Verification MathLaw
  • Swiss law requires the integration of ecological, social, and economic sustainability requirements into tender evaluations in the format of criteria that have to be fulfilled by a bidder.
  • We evaluate the system through a combination of automated quality checks, including an LLM-based evaluation component, and expert comparison against a manually curated gold standard.
Open paper

Match reason: Matches selected tags (Math, Expert Verification).

Score: 52% Sparse protocol signal Freshness: Warm Status: Fallback
Expert Verification Math
  • We provide empirical evidence through a detailed case study: the discovery of novel error representations and bounds for Hermite quadrature rules via systematic human-AI collaboration.
  • However, every step required rigorous human verification, mathematical intuition for problem formulation, and strategic direction.
Open paper

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