most citedBrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

2 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2025

Toward Training Superintelligent Software Agents through Self-Play SWE-RL

Yuxiang Wei, Zhiqing Sun, Emily McMilin +6

While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivity, their training data (e.g., GitHub i…

cs.CL2025

gpt-oss-120b & gpt-oss-20b Model Card

OpenAI, :, Sandhini Agarwal +124

We present gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models that push the frontier of accuracy and inference cost. The models use an efficient mixture-of-expert trans…

cs.CL2025★ 2 cited

BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

Jason Wei, Zhiqing Sun, Spencer Papay +7

We present BrowseComp, a simple yet challenging benchmark for measuring the ability for agents to browse the web. BrowseComp comprises 1,266 questions that require persistently nav…

cs.AI2024★ 1 cited

Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding

Shenghuan Sun, Alexander Schubert, Gregory M. Goldgof +4

Vision-Language Models (VLM) can support clinicians by analyzing medical images and engaging in natural language interactions to assist in diagnostic and treatment tasks. However,…

cs.CL2024★ 1 cited

Instruction-tuned Language Models are Better Knowledge Learners

Zhengbao Jiang, Zhiqing Sun, Weijia Shi +6

In order for large language model (LLM)-based assistants to effectively adapt to evolving information needs, it must be possible to update their factual knowledge through continued…