Best AI papers explained
A podcast by Enoch H. Kang
506 Episodes
-
Small Language Models are the Future of Agentic AI
Published: 07/10/2025 -
Activation Steering in Generative Settings via Contrastive Causal Mediation Analysis
Published: 06/10/2025 -
Eliciting Secret Knowledge from Language Models
Published: 06/10/2025 -
Temporal difference flow
Published: 06/10/2025 -
Personalized reasoning: just-in-time personalization and why LLMs fail at it
Published: 05/10/2025 -
Prompt Curriculum Learning for Efficient LLM Post-Training
Published: 05/10/2025 -
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
Published: 04/10/2025 -
Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Published: 04/10/2025 -
Learning to summarize user information for personalized reinforcement learning from human feedback
Published: 04/10/2025 -
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
Published: 03/10/2025 -
LIMI: Less is More for Agency
Published: 01/10/2025 -
LoRA Without Regret
Published: 01/10/2025 -
Actor-Critic without Actor: Critic-Guided Denoising for RL
Published: 29/09/2025 -
DELTA-Code: How Does RL Unlock and Transfer New Programming Algorithms in LLMs?
Published: 29/09/2025 -
Linear Transformers Implicitly Discover Unified Numerical Algorithms
Published: 29/09/2025 -
Regularizing Extrapolation in Causal Inference
Published: 27/09/2025 -
DoubleGen - Debiased Generative Modeling of Counterfactuals
Published: 27/09/2025 -
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Published: 27/09/2025 -
Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
Published: 27/09/2025 -
Learning without training: The implicit dynamics of in-context learning
Published: 24/09/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
