This podcast is focusing on sharing the papers on GenAI related topic, especially the SOTA (State of the Art) papers that are the foundations of GenAI work. It shows how these researches paved the way to the GenAI tools that we are using every day such as ChatGPT, Gemini, Claude Code etc.
EP481: Why Expert Imitation Breaks Small AI Models
Title: Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails
Source: http://arxiv.org/abs/2609.09134v1Summary:
This work establishes a foundational co-evolution paradigm for model training where evaluation harnesses and model parameters continuously adapt through on-policy feedback. It solves key limitations of traditional imitation learning, allowing smaller or weaker models to efficiently close the performance gap with frontier systems.
9 Oct 2026
EP480: Cloning Powerful AI Agents Just by Watching
Title: AgentLeak: Cloning Stronger LLM Agent Capabilities onto Weaker Agents Beyond Skill Stealing
Source: http://arxiv.org/abs/2609.07131v1
Summary:
This paper introduces a novel methodology for transferring complex agentic capabilities from frontier LLM agents to smaller, resource-efficient models beyond standard skill acquisition. It advances agent efficiency and distillation paradigms by enabling weaker models to replicate long-horizon reasoning and decision-making capabilities.
9 Oct 2026
EP479: Multi-Agent AI Debates Are Pure Theater
Title: A Layered Analysis of Disagreement And Answer Quality in Multi-Agent LLM Debate
Source: http://arxiv.org/abs/2609.08016v1
Summary:
This paper provides a foundational analysis of how disagreement dynamics and consensus formation impact solution accuracy in multi-agent LLM debate frameworks. Its structural insights directly inform the design of more robust multi-agent reasoning loops and collaborative alignment strategies.
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