1 citations · 1 across the 4 of their papers we have counts for
4 papers
What Makes a Terminal-Bench Task Hard? Separating Genuine Hardness from Fake-Hardness on an Adjudicated Agentic Corpus
Edward Lue Chee Lip, Boden Moraski, Tim Knappe +4
Frontier benchmarks need tasks that current models cannot solve. But a task that no model solves is not automatically a hard task. The same zero pass rate can come from a real capa…
TDFlow: Agentic Workflows for Test Driven Development
Kevin Han, Siddharth Maddikayala, Tim Knappe +3
We introduce TDFlow, a novel test-driven agentic workflow that frames repository-scale software engineering as a test-resolution task, specifically designed to solve human-written…
Scaling Natural-Language Graph-Based Test Time Compute for Automated Theorem Proving
Vincent Li, Tim Knappe, Yule Fu +2
Large language models have demonstrated remarkable capabilities in natural language processing tasks requiring multi-step logical reasoning capabilities, such as automated theorem…
Semantic Self-Consistency: Enhancing Language Model Reasoning via Semantic Weighting
Tim Knappe, Ryan Li, Ayush Chauhan +3
While large language models (LLMs) have rapidly improved their performance on a broad number of tasks, they still often fall short on reasoning tasks. As LLMs become more integrate…