We have 5 of 12 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Agents driven by large language models are increasingly deployed on long-horizon tasks, where they use tools and modify real workspaces. How well they perform depends as much on the harness around the model as on the model itself. Existing benchmarks measure downstream task success under a fixed harness, leaving harnes...
Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especially demanding because program logic, visual and audio content, interfaces, interaction and playability must function together in one executable artifact. Measuring this c...
WebCraftBench, an interactive benchmark for evaluating web application generation from a software testing perspective, is proposed and experiments show that coverage guidance improves exploration coverage and the model rankings remain stable when the judge model is replaced.
Human evaluation provides a direct measure of the quality of LLM-generated web applications. However, fitting human judgments through automated evaluation remains challenging. Static benchmarks can credit functionality that exists in source code but is unreachable at runtime. Interactive benchmarks exercise the applica...
GDPevo is presented, an evolution-native benchmark grounded in GDP-related enterprise workflows, together with the fully automated data pipeline that generates it, and the best evolved agents remain far below the fully informed oracle ceiling, indicating that the self-evolution ability of current agents remains far fro...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
