LLM News

Researchers propose Go-Browse, a method for training web agents through structured exploration that frames data collection as graph search. A 7B parameter language model fine-tuned on 10K trajectories achieves 21.7% success on the WebArena benchmark, outperforming GPT-4o mini by 2.4 percentage points.

Researchers at GAIR-NLP have published PC Agent-E, an agent training framework that achieves a 141% relative improvement in computer use tasks starting from only 312 human-annotated trajectories. The method uses Claude 3.7 Sonnet to synthesize alternative action decisions, and the resulting model outperforms Claude 3.7 Sonnet by 10% on WindowsAgentArena-V2.