Best AI papers explained
En podkast av Enoch H. Kang
550 Episoder
-
Preference Learning with Response Time
Publisert: 2.6.2025 -
Accelerating RL for LLM Reasoning with Optimal Advantage Regression
Publisert: 31.5.2025 -
Algorithms for reliable decision-making need causal reasoning
Publisert: 31.5.2025 -
Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality
Publisert: 31.5.2025 -
Distances for Markov chains from sample streams
Publisert: 31.5.2025 -
When and Why LLMs Fail to Reason Globally
Publisert: 31.5.2025 -
IDA-Bench: Evaluating LLMs on Interactive Guided Data Analysis
Publisert: 31.5.2025 -
No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference
Publisert: 31.5.2025 -
Accelerating RL for LLM Reasoning with Optimal Advantage Regression
Publisert: 31.5.2025 -
Statistical Inference for Online Algorithms
Publisert: 31.5.2025 -
Prismatic Synthesis for Diverse LLM Reasoning Data
Publisert: 31.5.2025 -
Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents
Publisert: 31.5.2025 -
The Agentic Economy
Publisert: 30.5.2025 -
Statistics for Large Language Models
Publisert: 29.5.2025 -
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search
Publisert: 29.5.2025 -
Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning
Publisert: 29.5.2025 -
Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL
Publisert: 29.5.2025 -
Value-Guided Search for Efficient Chain-of-Thought Reasoning
Publisert: 29.5.2025 -
Shallow Preference Signals: Large Language model aligns even better without truncated data?
Publisert: 29.5.2025 -
Gaming Tool Preferences in Agentic LLMs
Publisert: 29.5.2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
