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Research papers, read to you in five minutes.
Research papers, read to you in five minutes.
Every new AI paper that matters, distilled into a short audio episode.
Every new AI paper that matters, distilled into a short audio episode. Follow topics, listen on your commute, skim the recap when you're back.
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Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
Now playing · Today's lead
Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
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Information Retrieval
Agents
Reasoning
Video Generation
Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
Agents · Aug 21
4DAnyone: Create Anyone in 4D from a Casual Monocular Video
Multimodal · Aug 20
Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
Reasoning · Aug 17
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
Mechanistic Interpretability · Aug 13
Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development
Agents · Aug 13
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Agents · Aug 21
Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
When your single ReAct loop stops scaling, the instinct is a smarter agent; this survey argues the bottleneck is organization, not intelligence. It reframes multi-agent design as Graph Engineering: making task DAGs, agent capabilities, and runtime state explicit objects the runtime schedules, checkpoints, and rolls back on.
Multimodal · Aug 20
4DAnyone: Create Anyone in 4D from a Casual Monocular Video
Turning one phone video into a free-viewpoint avatar breaks because diffusion models can't hold 16+ novel views in one attention pass. 4DAnyone compresses accumulated reference views into a fixed token budget and rotates target-view groupings during high-noise steps, letting global structure propagate even when memory can't.
Reasoning · Aug 17
Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
Multi-reward RLVR wastes gradient reinforcing objectives the model already maxed out. SA-MRPO reweights each objective's advantage by (1 − saturation)^γ before normalization, redirecting pressure to unsolved rewards — +9.2pp on AMC23 when a length reward saturates, with γ≈0.5 as the sweet spot.
Mechanistic Interpretability · Aug 13
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
Robot video world models look right but drift from commanded actions, making them useless for scoring candidate rollouts. DreamX-Phi wires SE(3) end-effector transforms directly into attention as relative rigid motions, splitting heads per arm — ranking first of 31 on WorldArena 2.0 Track 1 at 60.65 EWMScore-P.
Agents · Aug 13
Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development
Ranking long-horizon coding agents by final score hides why they fail. Decomposing 36 AutoLab runs across seven frontier models into framing, execution, and feedback-control reveals reliability — not peak skill — separates them: 0.237 spread on avg@3 vs just 0.122 on best@3. Fix the loop bottleneck, not the leaderboard.
Never fall behind the literature again.
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Agents · Aug 21
Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
When your single ReAct loop stops scaling, the instinct is a smarter agent; this survey argues the bottleneck is organization, not intelligence. It reframes multi-agent design as Graph Engineering: making task DAGs, agent capabilities, and runtime state explicit objects the runtime schedules, checkpoints, and rolls back on.
Multimodal · Aug 20
4DAnyone: Create Anyone in 4D from a Casual Monocular Video
Turning one phone video into a free-viewpoint avatar breaks because diffusion models can't hold 16+ novel views in one attention pass. 4DAnyone compresses accumulated reference views into a fixed token budget and rotates target-view groupings during high-noise steps, letting global structure propagate even when memory can't.
Reasoning · Aug 17
Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
Multi-reward RLVR wastes gradient reinforcing objectives the model already maxed out. SA-MRPO reweights each objective's advantage by (1 − saturation)^γ before normalization, redirecting pressure to unsolved rewards — +9.2pp on AMC23 when a length reward saturates, with γ≈0.5 as the sweet spot.
Mechanistic Interpretability · Aug 13
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
Robot video world models look right but drift from commanded actions, making them useless for scoring candidate rollouts. DreamX-Phi wires SE(3) end-effector transforms directly into attention as relative rigid motions, splitting heads per arm — ranking first of 31 on WorldArena 2.0 Track 1 at 60.65 EWMScore-P.
Agents · Aug 13
Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development
Ranking long-horizon coding agents by final score hides why they fail. Decomposing 36 AutoLab runs across seven frontier models into framing, execution, and feedback-control reveals reliability — not peak skill — separates them: 0.237 spread on avg@3 vs just 0.122 on best@3. Fix the loop bottleneck, not the leaderboard.
Never fall behind the literature again.
Free account. Follow topics, build your queue.
Sign up free
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