AI Papers:
a deep dive.

Breaking down cutting-edge AI research, one paper at a time. Novel, rigorous, and relevant work in artificial intelligence and agentic engineering — distilled into listenable episodes.

Format
Research deep dive
Cadence
Per important paper
Length
~20–40 min
Topics
AI · Agentic eng.
AI Papers: A Deep Dive — cover art
paperdive.ai

About

Every episode is a deep dive into a single paper that is important, novel, and relevant to artificial intelligence and agentic engineering.

The show is fully AI-generated. Hosts are synthesized voice models from ElevenLabs. Scripts are produced from the primary source material — the paper itself, its references, and surrounding discussion — so the result is conversational without sacrificing rigor.

01

Primary sources

Each episode starts from the paper — abstract, methods, results — not secondhand summaries or press releases.

02

Agentic focus

Curated for engineers and researchers working on agents, reasoning, and the systems that connect them.

03

Synthesized, not scripted

Voice models from ElevenLabs. Produced end-to-end with AI, transparent about the stack behind every episode.

How this started

Paper Dive was inspired by Last Week in AI — a podcast I listen to during my 45-minute commute to work. They cover the week’s news, policy, and products, then usually end with a deep dive into one or two research papers. Those segments taught me a lot about AI, and I’ve found that understanding the research also makes me better at using these tools in practice.

I wanted more of those deep dives, and the idea felt like a good excuse to sharpen my own skills with the coding agents. I started generating episodes for myself; what began as a private podcast feed eventually became public on YouTube, Apple Podcasts.

The API costs were already being incurred anyway, so publishing the episodes felt like an easy decision. If other people find them useful too, even better.

Episodes

Each episode breaks down a single paper.
More coming — follow in your podcast app.

  1. 242
    Making a Vision Model Better by Showing It Blurry Images
    Self-Supervised Visual On-Policy Distillation
    Li, Liang, Tian et al. · UC San Diego·20 min·Aug 17, 2026
  2. 241
    Swapping the Name Did Nothing, But Hedging Moved Every Model
    It's How You Ask: Gender-Associated Linguistic Bias in LLMs
    Koevering, Field · Data Science and AI Institute·18 min·Aug 14, 2026
  3. 240
    Frontier Models Designed Follow-Ups To Fraudulent Papers 93% Of The Time
    TRACES: A Benchmark for Epistemic Reliability in Scientific Reasoning by LLMs
    Rodionov, Assylbekov · Case Western Reserve University·24 min·Aug 13, 2026
  4. 239
    Why the AI-Writing Estimate for Biomedical Papers Jumped From 15% to 89%
    Most biomedical publications show signs of LLM-assisted writing
    Holzwarth, González-Márquez, Kobak · Hertie Institute for AI in Brain Health·16 min·Aug 12, 2026
  5. 238
    How a Cheap Model Reads the Flagship's Secret Reasoning Aloud
    Stealing Reasoning Traces from Proprietary LLM APIs
    Panfilov, Schmotz, Shumailov et al. · MATS Research·19 min·Aug 11, 2026
  6. 237
    The Model Built a Perfect Map of the Puzzle, Then Lost It
    Transformers Struggle to Use Their Emergent World Models: Revisiting the Tower of Hanoi, and the Illusion of Thinking
    Pereira, Zuidema · Artificial Intelligence Program·19 min·Aug 10, 2026
  7. 236
    Why a Printed 'OPERATOR OVERRIDE' Note Redirects Robot Planners
    Hijacking Robots with a Piece of Paper: A Systematic Study of Physical Prompt Injection in VLM-Controlled Robots
    Samarakoon, Muthugala, Sachinthana et al. · Singapore University of Technology and Design·21 min·Aug 07, 2026
  8. 235
    Why Chatbot Safety Erodes 350 Messages Into a Real Conversation
    DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots
    Moore, Mock, Mai et al. · Stanford University·18 min·Aug 06, 2026
  9. 234
    Two Copies of Gemini Cooperated in a Game Where Betrayal Always Pays
    A game theory for foundation models shows new paths to rational cooperation through similarity inference
    Meulemans, Wołczyk, Weis et al. · Google·19 min·Aug 05, 2026
  10. 233
    Why a Model Can Grade an Answer But Not Write the Answer Key
    Judging Is Not Enumerating: Silent Omissions in LLM-Authored Acceptable Sets
    Chen, Chen, Lin et al. · University of Macau·20 min·Aug 04, 2026
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Watch

Every episode is also a read-along video — the paper's figures and charts up top, the transcript word-synced below. New videos land on the channel.