Best AI papers explained
A podcast by Enoch H. Kang
512 Episodio
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A foundation model to predict and capture human cognition
Pubblicato: 04/08/2025 -
Generative Recommendation with Semantic IDs: A Practitioner’s Handbook
Pubblicato: 04/08/2025 -
Hierarchical Reasoning Model
Pubblicato: 04/08/2025 -
Test-time Offline Reinforcement Learning on Goal-related Experience
Pubblicato: 04/08/2025 -
Interpreting Chain of Thought: A Walkthrough and Discussion
Pubblicato: 04/08/2025 -
The wall confronting large language models
Pubblicato: 04/08/2025 -
COLLABLLM: LLMs From Passive to Collaborative
Pubblicato: 31/07/2025 -
A decade's battle on dataset bias: are we there yet?
Pubblicato: 29/07/2025 -
GEPA: Generative Feedback for AI System Optimization
Pubblicato: 29/07/2025 -
From AI-Curious to AI-First: Engineering Production AI Systems
Pubblicato: 28/07/2025 -
Context Engineering: Beyond Simple Prompting to LLM Architecture
Pubblicato: 28/07/2025 -
Agentic Misalignment: LLMs as Insider Threats
Pubblicato: 28/07/2025 -
Small Language Models: Future of Agentic AI
Pubblicato: 28/07/2025 -
Learning without training: The implicit dynamics of in-context learning
Pubblicato: 28/07/2025 -
Inverse Scaling in Test-Time Compute
Pubblicato: 28/07/2025 -
LLM Economist: Large Population Models and Mechanism Design in Multi-Agent Generative Simulacra
Pubblicato: 28/07/2025 -
Microsoft's Blueprint: AI, Quantum, and the Agentic Future
Pubblicato: 26/07/2025 -
Zuckerberg's AI Vision Analyzed
Pubblicato: 26/07/2025 -
Inside Claude: Scaling, Agency, and Interpretability
Pubblicato: 26/07/2025 -
Personalized language modeling from personalized human feedback
Pubblicato: 26/07/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
