2 citations · 3 across the 15 of their papers we have counts for
7 papers · 1 filter
PRInTS: Reward Modeling for Long-Horizon Information Seeking
Jaewoo Lee, Archiki Prasad, Justin Chih-Yao Chen +3
Information-seeking is a core capability for AI agents, requiring them to gather and reason over tool-generated information across long trajectories. However, such multi-step infor…
One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration
Zaid Khan, Archiki Prasad, Elias Stengel-Eskin +2
Symbolic world modeling requires inferring and representing an environment's transitional dynamics as an executable program. Prior work has focused on largely deterministic environ…
OpenThoughts: Data Recipes for Reasoning Models
Etash Guha, Ryan Marten, Sedrick Keh +47
Reasoning models have made rapid progress on many benchmarks involving math, code, and science. Yet, there are still many open questions about the best training recipes for reasoni…
Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems
Zaid Khan, Elias Stengel-Eskin, Archiki Prasad +2
Scientists often infer abstract procedures from specific instances of problems and use the abstractions to generate new, related instances. For example, programs encoding the forma…
DWIM: Towards Tool-aware Visual Reasoning via Discrepancy-aware Workflow Generation & Instruct-Masking Tuning
Fucai Ke, Vijay Kumar B G, Xingjian Leng +6
Visual reasoning (VR), which is crucial in many fields for enabling human-like visual understanding, remains highly challenging. Recently, compositional visual reasoning approaches…
MutaGReP: Execution-Free Repository-Grounded Plan Search for Code-Use
Zaid Khan, Ali Farhadi, Ranjay Krishna +3
When a human requests an LLM to complete a coding task using functionality from a large code repository, how do we provide context from the repo to the LLM? One approach is to add…
Learning to Generate Unit Tests for Automated Debugging
Archiki Prasad, Elias Stengel-Eskin, Justin Chih-Yao Chen +2
Unit tests (UTs) play an instrumental role in assessing code correctness as well as providing feedback to large language models (LLMs), motivating automated test generation. Howeve…