Best AI papers explained
A podcast by Enoch H. Kang
515 Episodes
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Understanding Prompt Tuning and In-Context Learning via Meta-Learning
Published: 11/10/2025 -
MLPs Learn In-Context on Regression and Classification tasks
Published: 11/10/2025 -
Is Pre-Training Truly Better than Meta-Learning?
Published: 11/10/2025 -
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Published: 11/10/2025 -
Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs
Published: 9/10/2025 -
Learning dynamics of LLM finetuning
Published: 9/10/2025 -
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Published: 9/10/2025 -
OpenAI Agent Builder and n8n: Orchestrating Reasoning Versus Automating Process
Published: 8/10/2025 -
Training Agents Inside of Scalable World Models
Published: 8/10/2025 -
Small Language Models are the Future of Agentic AI
Published: 7/10/2025 -
Activation Steering in Generative Settings via Contrastive Causal Mediation Analysis
Published: 6/10/2025 -
Eliciting Secret Knowledge from Language Models
Published: 6/10/2025 -
Temporal difference flow
Published: 6/10/2025 -
Personalized reasoning: just-in-time personalization and why LLMs fail at it
Published: 5/10/2025 -
Prompt Curriculum Learning for Efficient LLM Post-Training
Published: 5/10/2025 -
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
Published: 4/10/2025 -
Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Published: 4/10/2025 -
Learning to summarize user information for personalized reinforcement learning from human feedback
Published: 4/10/2025 -
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
Published: 3/10/2025 -
LIMI: Less is More for Agency
Published: 1/10/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
