Best AI papers explained
Un pódcast de Enoch H. Kang
525 Episodo
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LoRe: Low-Rank Reward Modeling for Personalized LLMs
Publicado: 26/4/2025 -
ParaPO: Reducing Language Model Verbatim Reproduction
Publicado: 26/4/2025 -
Test-Time RL: Self-Evolving LLMs via Majority Voting Rewards
Publicado: 25/4/2025 -
Tina: Tiny LoRA Reasoning Models
Publicado: 25/4/2025 -
Evaluating large language models in theory of mind tasks
Publicado: 25/4/2025 -
QUEST: Quality Sampling for Machine Translation
Publicado: 24/4/2025 -
Offline Preference Learning via Simulated Trajectory Feedback
Publicado: 24/4/2025 -
Reasoning Elicitation in Language Models via Counterfactual Feedback
Publicado: 24/4/2025 -
Eliciting Human Preferences with Language Models
Publicado: 24/4/2025 -
Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning
Publicado: 24/4/2025 -
γ-Bench: Evaluating LLMs in Multi-Agent Games
Publicado: 24/4/2025 -
DRAFT: Self-Driven LLM Tool Mastery via Documentation Refinement
Publicado: 24/4/2025 -
Optimal Prediction Sets for Enhanced Human-AI Accuracy
Publicado: 24/4/2025 -
Self-Correction via Reinforcement Learning for Language Models
Publicado: 24/4/2025 -
Tractable Multi-Agent Reinforcement Learning through Behavioral Economics
Publicado: 24/4/2025 -
Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement
Publicado: 24/4/2025 -
Iterative Nash Policy Optimization for Language Model Alignment
Publicado: 24/4/2025 -
SycEval: Benchmarking LLM Sycophancy in Mathematics and Medicine
Publicado: 23/4/2025 -
Stack AI: Democratizing Enterprise AI Development
Publicado: 22/4/2025 -
Evaluating Modern Recommender Systems: Challenges and Future Directions
Publicado: 22/4/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
