Concept · 7 episode(s)

Multi-Hop Reasoning

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Definition

Multi-hop reasoning is reasoning that requires combining several pieces of evidence in sequence — finding A, then using A to find B, then using B to answer the question. It’s a recurring benchmark category because single-hop retrieval makes most QA tasks too easy.

Episodes covering this

  1. 212
    The Fact Was in the Wrong Drawer: Why Fine-Tuned Models Can't Reason With What They Know
    Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning
    Dai, Rao, Wang et al. · HKUST(GZ)·14 min·Jul 10, 2026
  2. 183
    Why You Can't Fine-Tune Foresight Into an AI Agent
    Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning
    Zhang, Zhou, Qiao et al. · Fudan University / Shanghai Innovation Institute / Tencent Youtu Lab·23 min·Jun 29, 2026
  3. 157
    When an AI Coding Agent Drives a Phone Through the Terminal, No Screen Needed
    Beyond the GUI Paradigm: Do Mobile Agents Need the Phone Screen?
    Gu, Jiang, Guo et al. · Mila–Québec AI Institute / Concordia University·24 min·Jun 19, 2026
  4. 104
    How Making a Research Agent Smarter Quietly Makes It Leak Your Secrets
    MosaicLeaks:Privacy Risks in Querying-in-the-Open for Deep Research Agents
    Gurung, Gella, Drouin et al. · University of Edinburgh·25 min·Jun 01, 2026
  5. 098
    Finding Millions of Readable Concepts Inside a Real, Deployed AI Model
    Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet
    Templeton, Conerly, Marcus et al. · Anthropic·28 min·May 29, 2026
  6. 021
    Ten Thousand Examples Beat the Full Industrial Pipeline for Search Agents
    OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories
    Du, Ye, Tang et al. · Shanghai Jiao Tong University·14 min·May 06, 2026
  7. 011
    When RL Actually Teaches Agents Something New, And When It Doesn't
    Does RL Expand the Capability Boundary of LLM Agents? A PASS@(k,T) Analysis
    Zhai, Yan, Shao et al. · Fudan University·23 min·May 02, 2026

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