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Prior to joining Palantir, I have been a Professor of Computer Science at Harvard, an…
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Russ Salakhutdinov
New work on Rethinking Thinking Tokens: LLMs as Improvement Operators: https://lnkd.in/errhNuuz Reasoning training encourages LLMs to produce long chains of thought (CoT), improving accuracy via self-checking but increasing context length, compute cost, and latency. This work studies whether frontier models can achieve better trade-offs, higher accuracy with lower cost. The paper develops a simple yet effective Parallel-Distill-Refine (PDR) procedure: Generate diverse drafts in parallel, Distill them into a compact textual workspace, and Refine conditioned on this workspace. This decouples context length from total token count, allowing control over compute via parallelism. PDR yields higher accuracy than long CoT at lower latency. Training an 8B model with RL to align with PDR further shifts the Pareto frontier. On math benchmarks, PDR achieves +11% (AIME 2024) and +9% (AIME 2025) over single-pass baselines. With Lovish Madaan, Aniket Didolkar, Suchin Gururangan, John Quan, Ruan Silva, Manzil Zaheer, Sanjeev Arora, and Anirudh Goyal.
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Alex Leung
Go to sleep. Wake up to results. The human writes Markdown. The AI runs 100 experiments overnight. On one GPU. Karpathy's autoresearch is what ML research looks like now. You don't tune hyperparameters anymore. You design the arena and let the agent iterate inside it. Same pattern we landed on building our own refinement agent. Strict targets to optimize towards. Tight constraints, fast feedback, let it loop. Our accuracy for certain document formats went from 22% to 100% overnight. Engineer the environment. Constrain the scope. Let the agent run.
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Michael Ryaboy
Thanks to the resurgence of RL, LLMs are finally able to reliably coordinate tools and reasoning to do high-precision retrieval. Companies like Happenstance, Clado, and Mintlify have already shifted to agentic search, and it's only a matter of time until anything less feels broken to users. Link to full blog in comments.
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