Skip to content

Researcher Tools

Human Feedback and Eval Paper Explorer

A focused feed for RLHF, preference data, rater protocols, agent evaluation, and LLM-as-judge research. Every paper includes structured metadata for quick triage.

Total papers: 3 Search mode: keyword Shortlist (0) RSS

Featured Papers

Popular high-signal papers with direct links to full protocol pages.

Browse by Topic

Jump directly into tag and hub pages to crawl deeper content clusters.

Popular Tags

Top Protocol Hubs

Weekly Eval Paper Digest

The top RLHF, evaluation, and human feedback papers — curated and summarized every Friday.

No spam. Unsubscribe anytime.

Start Here By Objective

Pick your immediate research objective and jump directly to high-signal pages, not generic search.

Scale Your Evaluation Team

Need human evaluators for your benchmark or preference study? OpenTrain sources pre-vetted domain experts into your annotation pipeline.

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

Score: 100% High protocol signal Freshness: Hot Status: Ready
Rubric Rating Automatic Metrics Long Horizon General
  • Multi-agent debate (MAD), and more broadly closed-system reasoning where agents iteratively transform each other's outputs, tends to preserve answer accuracy while degrading the reasoning behind those answers.
  • An R6 cohort study (Korean n=10x30 FEVER; English n=3x200 SciFact) finds inter-rater Fleiss kappa <= +0.018 with 0.8-1.4 Likert intra-rater shifts across language and domain -- the human agreement that faithfulness metrics have been…
Open paper

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

Score: 100% High protocol signal Freshness: Warm Status: Ready
Pairwise Preference Automatic Metrics Long Horizon General
  • Autonomous agents operating in continuous environments must decide not only what to do, but when to act.
  • High spread indicates a branching, uncertain future and drives the agent to act sooner; low spread signals predictability and permits longer rest intervals.
Open paper
From Days to Minutes: An Autonomous AI Agent Achieves Reliable Clinical Triage in Remote Patient Monitoring

Seunghwan Kim, Tiffany H. Kung, Heena Verma, Dilan Edirisinghe, Kaveh Sedehi, Johanna Alvarez · Mar 10, 2026

Citations: 0

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

Score: 100% High protocol signal Freshness: Warm Status: Ready
Expert Verification Automatic Metrics Long Horizon Medicine
  • Results: Against a human majority-vote standard (N=467), the agent achieved 95.8% emergency sensitivity and 88.5% sensitivity for all actionable alerts (85.7% specificity).
  • In LOO analysis, the agent outperformed every clinician in emergency sensitivity (97.5% vs.
Open paper

Protocol Hubs

Get Started

Join the #1 Platform for AI Training Talent

Where top AI builders and expert AI Trainers connect to build the future of AI.
Self-Service
Post a Job
Post your project and get a shortlist of qualified AI Trainers and Data Labelers. Hire and manage your team in the tools you already use.
Managed Service
For Large Projects
Done-for-You
We recruit, onboard, and manage a dedicated team inside your tools. End-to-end operations for large or complex projects.
For Freelancers
Join as an AI Trainer
Find AI training and data labeling projects across platforms, all in one place. One profile, one application process, more opportunities.