Deep Papers

Science & Technology News

Deep Papers is a podcast series featuring deep dives on today’s most important AI papers and research. Hosted by Arize AI founders and engineers, each episode profiles the people and techniques behind cutting-edge breakthroughs in machine learning.

Episodes

CUGA Agent: From Benchmarks to Business Impact of IBM's Generalist Agent

TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture

Meta AI Researcher Explains ARE and Gaia2: Scaling Up Agent Environments and Evaluations

Georgia Tech's Santosh Vempala Explains Why Language Models Hallucinate, His Research With OpenAI

Atropos Health’s Arjun Mukerji, PhD, Explains RWESummary: A Framework and Test for Choosing LLMs to Summarize Real-World Evidence (RWE) Studies

Stan Miasnikov, Distinguished Engineer, AI/ML Architecture, Consumer Experience at Verizon Walks Us Through His New Paper

Small Language Models are the Future of Agentic AI

Watermarking for LLMs and Image Models

Self-Adapting Language Models: Paper Authors Discuss Implications

The Illusion of Thinking: What the Apple AI Paper Says About LLM Reasoning

Accurate KV Cache Quantization with Outlier Tokens Tracing

Scalable Chain of Thoughts via Elastic Reasoning

Sleep-time Compute: Beyond Inference Scaling at Test-time

LibreEval: The Largest Open Source Benchmark for RAG Hallucination Detection

AI Benchmark Deep Dive: Gemini 2.5 and Humanity's Last Exam

Model Context Protocol (MCP)

AI Roundup: DeepSeek’s Big Moves, Claude 3.7, and the Latest Breakthroughs

How DeepSeek is Pushing the Boundaries of AI Development

Multiagent Finetuning: A Conversation with Researcher Yilun Du

Training Large Language Models to Reason in Continuous Latent Space