Best AI papers explained
A podcast by Enoch H. Kang
550 Episodio
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Learning dynamics of LLM finetuning
Pubblicato: 09/10/2025 -
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Pubblicato: 09/10/2025 -
OpenAI Agent Builder and n8n: Orchestrating Reasoning Versus Automating Process
Pubblicato: 08/10/2025 -
Training Agents Inside of Scalable World Models
Pubblicato: 08/10/2025 -
Small Language Models are the Future of Agentic AI
Pubblicato: 07/10/2025 -
Activation Steering in Generative Settings via Contrastive Causal Mediation Analysis
Pubblicato: 06/10/2025 -
Eliciting Secret Knowledge from Language Models
Pubblicato: 06/10/2025 -
Temporal difference flow
Pubblicato: 06/10/2025 -
Personalized reasoning: just-in-time personalization and why LLMs fail at it
Pubblicato: 05/10/2025 -
Prompt Curriculum Learning for Efficient LLM Post-Training
Pubblicato: 05/10/2025 -
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
Pubblicato: 04/10/2025 -
Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Pubblicato: 04/10/2025 -
Learning to summarize user information for personalized reinforcement learning from human feedback
Pubblicato: 04/10/2025 -
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
Pubblicato: 03/10/2025 -
LIMI: Less is More for Agency
Pubblicato: 01/10/2025 -
LoRA Without Regret
Pubblicato: 01/10/2025 -
Actor-Critic without Actor: Critic-Guided Denoising for RL
Pubblicato: 29/09/2025 -
DELTA-Code: How Does RL Unlock and Transfer New Programming Algorithms in LLMs?
Pubblicato: 29/09/2025 -
Linear Transformers Implicitly Discover Unified Numerical Algorithms
Pubblicato: 29/09/2025 -
Regularizing Extrapolation in Causal Inference
Pubblicato: 27/09/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
