From the 1 of 69 linked papers with an AI index.
1 citations · 1 across the 15 of their papers we have counts for
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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…
Reasoning Curriculum: Bootstrapping Broad LLM Reasoning from Math
Bo Pang, Deqian Kong, Silvio Savarese +2
Reinforcement learning (RL) can elicit strong reasoning in large language models (LLMs), yet most open efforts focus on math and code. We propose Reasoning Curriculum, a simple two…
GTA1: GUI Test-time Scaling Agent
Yan Yang, Dongxu Li, Yutong Dai +12
Graphical user interface (GUI) agents autonomously complete tasks across platforms (\eg, Linux) by sequentially decomposing user instructions into action proposals that iteratively…
SCUBA: Salesforce Computer Use Benchmark
Yutong Dai, Krithika Ramakrishnan, Jing Gu +8
We introduce SCUBA, a benchmark designed to evaluate computer-use agents on customer relationship management (CRM) workflows within the Salesforce platform. SCUBA contains 300 task…
UserRL: Training Interactive User-Centric Agent via Reinforcement Learning
Cheng Qian, Zuxin Liu, Akshara Prabhakar +10
Reinforcement learning (RL) has shown promise in training agentic models that move beyond static benchmarks to engage in dynamic, multi-turn interactions. Yet, the ultimate value o…
Contra4: Evaluating Contrastive Cross-Modal Reasoning in Audio, Video, Image, and 3D
Artemis Panagopoulou, Le Xue, Honglu Zhou +6
Real-world decision-making often begins with identifying which modality contains the most relevant information for a given query. While recent multimodal models have made impressiv…