Microsoft Research

Microsoft Research Asia introduces the Harnessed Agentic RL paradigm and open-sources a rebuilt Agent Lightning v1.0, in which the same agent harness used in deployment participates directly in reinforcement learning through an LLM proxy; the framework is about 3,500 lines of code, runs agents as standard Kubernetes jobs, and on an end-to-end coding agent pipeline built on SWE-smith, mini-SWE-agent, and Qwen3.5-9B, roughly 6,000 training samples raise Pass@1 on SWE-bench Verified from 41.8% to 56.4%, an absolute gain of 14.6 percentage points.

Microsoft Research Asia introduces the Harnessed Agentic RL paradigm and open-sources a rebuilt Agent Lightning v1.0, in which the same agent harness used in deployment participates directly in reinforcement learning through an LLM proxy; the framework is about 3,500 lines of code, runs agents as standard Kubernetes jobs, and on an end-to-end coding agent pipeline built on SWE-smith, mini-SWE-agent, and Qwen3.5-9B, roughly 6,000 training samples raise Pass@1 on SWE-bench Verified from 41.8% to 56.4%, an absolute gain of 14.6 percentage points.

Microsoft Research introduces Quine, a research system combining a world model of biology trained jointly across modalities including sequence, structure, function, cellular state, and imaging with a harness connecting scientific tools, literature, the wet lab, and researchers; with the Broad Institute it used the system in pancreatic ductal adenocarcinoma (PDAC) to predict and prioritize thousands of compounds by their potential to shift tumor cells between therapeutically relevant states, wet-lab assays showed Quine's highest-ranked compounds produced the largest intended shifts, the whole process from narrowing the search space to prioritizing a handful of candidates took just one weekend, and the experiments also bore out the model's prediction of a distinct third phenotype.

Microsoft Research introduces Quine, a research system combining a world model of biology trained jointly across modalities including sequence, structure, function, cellular state, and imaging with a harness connecting scientific tools, literature, the wet lab, and researchers; with the Broad Institute it used the system in pancreatic ductal adenocarcinoma (PDAC) to predict and prioritize thousands of compounds by their potential to shift tumor cells between therapeutically relevant states, wet-lab assays showed Quine's highest-ranked compounds produced the largest intended shifts, the whole process from narrowing the search space to prioritizing a handful of candidates took just one weekend, and the experiments also bore out the model's prediction of a distinct third phenotype.