2 citations · 4 across the 5 of their papers we have counts for
4 papers · 1 filter
Projected Distillation: On Learning to Solve Hard Problems from Close, Correct Targets
Shripad V. Deshmukh, Christian Bock, Kangrui Ruan +4
On-policy learning is central to post-training: training on a model's own generations limits distribution shift and helps preserve existing capabilities. On hard problems, however,…
ANTE: Anticipate, Then Execute -- Learning Internal World Models for Coding Agents from Verified Beliefs
Yi Ge, Kangrui Ruan, Jifan Chen +6
Rapid advances in large language models have made software engineering agents capable of tackling complex coding tasks. Within a containerized environment, a coding agent receives…
Teaching Agents to Code Reliably
Muhammad Ahmed Mohsin, Myeongsoo Kim, Kangrui Ruan +3
Autonomous coding agents solve repository issues by reading code, running commands, editing files, and submitting patches. Extra inference-time compute yields gains only when it pr…
A Causal Bootstrap for Diverse Image Generation under Unobserved Confounding
Jingyuan Chen, Kangrui Ruan, Junzhe Zhang
Deep generative models reproduce the observational distribution underlying the training data, which, in turn, inherit any spurious associations it contains. A common source is an u…