Best AI papers explained

Podcast készítő Enoch H. Kang

534 Epizód

Understanding neural networks through sparse circuits
Közzétéve: 2025. 11. 14.
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Közzétéve: 2025. 11. 14.
Multi-Agent Evolve: LLM Self-Improvement Through Co-Evolution
Közzétéve: 2025. 11. 14.
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
Közzétéve: 2025. 11. 14.
PREFDISCO: Evaluating Proactive Personalization through Interactive Preference Discovery
Közzétéve: 2025. 11. 12.
Reusing pre-training data at test time is a compute multiplier
Közzétéve: 2025. 11. 10.
Scaling Agent Learning via Experience Synthesis
Közzétéve: 2025. 11. 09.
Continuous Autoregressive Language Models
Közzétéve: 2025. 11. 08.
Toward a Theory of Agents as Tool-Use Decision-Makers
Közzétéve: 2025. 11. 07.
Nested Learning: The Illusion of Deep Learning Architectures
Közzétéve: 2025. 11. 05.
GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding
Közzétéve: 2025. 11. 05.
Beyond a million tokens: benchmarking and enhancing long-term memory in llms
Közzétéve: 2025. 11. 04.
Agentic Economic Modeling
Közzétéve: 2025. 11. 03.
Emergent Introspective Awareness in Large Language Models
Közzétéve: 2025. 11. 03.
Can Large reasoning models self-train?
Közzétéve: 2025. 11. 01.
ALITA-G: Self-Evolving Generative Agent for Agent Generation
Közzétéve: 2025. 11. 01.
Self-improving LLM agents at test-time
Közzétéve: 2025. 10. 30.
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Közzétéve: 2025. 10. 30.
Language models are injective and hence invertible
Közzétéve: 2025. 10. 30.
ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory
Közzétéve: 2025. 10. 29.

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534 Epizód

Understanding neural networks through sparse circuits

Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning

Multi-Agent Evolve: LLM Self-Improvement Through Co-Evolution

LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics

PREFDISCO: Evaluating Proactive Personalization through Interactive Preference Discovery

Reusing pre-training data at test time is a compute multiplier

Scaling Agent Learning via Experience Synthesis

Continuous Autoregressive Language Models

Toward a Theory of Agents as Tool-Use Decision-Makers

Nested Learning: The Illusion of Deep Learning Architectures

GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding

Beyond a million tokens: benchmarking and enhancing long-term memory in llms

Agentic Economic Modeling

Emergent Introspective Awareness in Large Language Models

Can Large reasoning models self-train?

ALITA-G: Self-Evolving Generative Agent for Agent Generation

Self-improving LLM agents at test-time

Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization

Language models are injective and hence invertible

ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory