4 citations · 12 across the 17 of their papers we have counts for
5 papers · 1 filter
TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation
Akash Gokul, Srijan Bansal, Yingbo Zhou +1
Test-case generation is critical but remains challenging for language models. Existing test-time scaling methods either isolate candidates or aggregate traces, which do not scale t…
MobileWorldBench: Towards Semantic World Modeling For Mobile Agents
Shufan Li, Konstantinos Kallidromitis, Akash Gokul +3
World models have shown great utility in improving the task performance of embodied agents. While prior work largely focuses on pixel-space world models, these approaches face prac…
Self-Abstraction from Grounded Experience for Plan-Guided Policy Refinement
Hiroaki Hayashi, Bo Pang, Wenting Zhao +6
Large language model (LLM) based agents are increasingly used to tackle software engineering tasks that require multi-step reasoning and code modification, demonstrating promising…
CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules
Hung Le, Hailin Chen, Amrita Saha +3
Large Language Models (LLMs) have already become quite proficient at solving simpler programming tasks like those in HumanEval or MBPP benchmarks. However, solving more complex and…
REX: Rapid Exploration and eXploitation for AI Agents
Rithesh Murthy, Shelby Heinecke, Juan Carlos Niebles +12
In this paper, we propose an enhanced approach for Rapid Exploration and eXploitation for AI Agents called REX. Existing AutoGPT-style techniques have inherent limitations, such as…