Deep Papers

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We dive into the latest paper from Google and a team of academic researchers: "TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture."Hear from one of the paper's authors — Yongchao Chen, Research Scientist — walks through the research and its implications. The paper proposes T‮…

In our latest paper reading, we had the pleasure of hosting Grégoire Mialon — Research Scientist at Meta Superintelligence Labs — to walk us through Meta AI’s groundbreaking paper titled “ARE: scaling up agent environments and evaluations" and the new ARE and Gaia2 frameworks. Learn more abo‮…

Santosh Vempala, Frederick Storey II Chair of Computing and Distinguished Professor in the School of Computer Science at Georgia Tech, explains his paper co-authored by OpenAI's Adam Tauman Kalai, Ofir Nachum, and Edwin Zhang. Read the paper: Sign up for future AI research paper readings and ‮…

Large language models are increasingly used to turn complex study output into plain-English summaries. But how do we know which models are safest and most reliable for healthcare?  In this most recent community AI research paper reading, Arjun Mukerji, PhD – Staff Data Scientist at Atropos Health ‮…

This episode dives into "Category-Theoretic Analysis of Inter-Agent Communication and Mutual Understanding Metric in Recursive Consciousness." The paper presents an extension of the Recursive Consciousness framework to analyze communication between agents and the inevitable loss of meani‮…

We had the privilege of hosting Peter Belcak – an AI Researcher working on the reliability and efficiency of agentic systems at NVIDIA – who walked us through his new paper making the rounds in AI circles titled “Small Language Models are the Future of Agentic AI.”The paper posits that small langu‮…

In this AI research paper reading, we dive into "A Watermark for Large Language Models" with the paper's author John Kirchenbauer.  This paper is a timely exploration of techniques for embedding invisible but detectable signals in AI-generated text. These watermarking strategies aim‮…

The authors of the new paper *Self-Adapting Language Models (SEAL)* shared a behind-the-scenes look at their work, motivations, results, and future directions. The paper introduces a novel method for enabling large language models (LLMs) to adapt their own weights using self-generated data and tra‮…

This week we discuss The Illusion of Thinking, a new paper from researchers at Apple that challenges today’s evaluation methods and introduces a new benchmark: synthetic puzzles with controllable complexity and clean logic.  Their findings? Large Reasoning Models (LRMs) show surprising failure mod‮…