UW NLP

Kshitish Ghate Verified account @GhateKshitish · Nov 3

New #NeurIPS2026 paper 🧵
We introduce 🌟 Deep Reasoning 🌟, an approach for building just-in-time agentic harnesses for solving diverse reasoning problems.
Inspired by human cognition, we recursively decompose tasks into atomic units of formal and associative reasoning steps. We instantiate deep reasoning through DOLORES, our structured meta-harness:

DOLORES achieves ~25% higher accuracy against SOTA baselines (including RLMs and Deep Research) 🚀
enabling 8B models to outperform 32B variants of the same family 🤖
…all training-free!

🧵 below,

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Stella Li Verified account @StellaLisy · Oct 8

We introduce ExploreNet🔍 for learnable exploration in diffusion RL.

ExploreNet learns an adaptive exploration distribution conditioned on the current state, rewarded by the diversity of the rollouts.

➡️ Faster, more targeted learning in diffusion GRPO.

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WAI Verified account @waiorg · Oct 2

We recently released Context Language Models (CLMs), and got many questions on KV Cache.

Our latest blog explains
1). how we measure cache-ware FLOPs
2). how to efficiently serve CLM

wai-org.com/blog/clm/

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Nathan Lambert Verified account @natolambert · Jul 29

New podcast/lecture combo -- a case study in the messy details of Olmo 3 post training & DPO with @scottgeng00. It's rare to make time for these discussions, but we cover:

What it takes for a research idea to make it into a (near) frontier model.
The messy side of DPO (usually data).
Organizational challenges in multi-stage post-training recipes.
Reflections on where research is heading today, and how people should think of DPO.
DPO fundamentals (once more)
Other topics.

Scott is one of the great student's I've had the pleasure of working with for a few years!

Chapters:

00:00 Introduction
04:32 Preference Tuning Basics
08:21 The DPO-Algorithm Zoo
17:06 Scaling Preference Data
21:55 Delta Learning Hypothesis
32:30: Applying it to Olmo 3
36:08 Challenge 1: Data Details
47:17 Challenge 2: Organization Management
51:45 Challenge 3: Scaling Issues
59:15 The Future of Academic Research

Excited to keep making this content under the motivation of my book. Really plugging away now :)

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Prime Intellect @PrimeIntellect · Jul 22

Scaling agentic RL environments: today we're publishing 365,000+ tasks for SWE, terminal, and search agents - 23 tasksets behind one API, one sandbox lifecycle, one command.

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