14 papers
R2V Agent: Teaching SLMs When to Ask for Help
Raghu Vamshi Hemadri, Humaira Firdowse Mohammed, Rishabh Maheshwary +5
Efficient agentic systems should incur expensive frontier-model costs only on decisions where a cheaper local model is likely to fail. Existing LLM cascades usually route whole que…
AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs
Hoang Nguyen, Sidharth Surapaneni, Akshay Kalkunte +9
Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and non-standardized toolkits that limit fair comparison and s…
Therefore I am. I Think
Esakkivel Esakkiraja, Sai Rajeswar, Denis Akhiyarov +1
We consider the question: when a large language reasoning model makes a choice, did it think first and then decide to, or decide first and then think? In this paper, we present evi…
Terminal Agents Suffice for Enterprise Automation
Patrice Bechard, Orlando Marquez Ayala, Emily Chen +5
There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomously. Among the approaches explored are t…
CUA-Suite: Massive Human-annotated Video Demonstrations for Computer-Use Agents
Xiangru Jian, Shravan Nayak, Kevin Qinghong Lin +5
Computer-use agents (CUAs) hold great promise for automating complex desktop workflows, yet progress toward general-purpose agents is bottlenecked by the scarcity of continuous, hi…
EnterpriseOps-Gym: Environments and Evaluations for Stateful Agentic Planning and Tool Use in Enterprise Settings
Shiva Krishna Reddy Malay, Shravan Nayak, Jishnu Sethumadhavan Nair +6
Large language models are shifting from passive information providers to active agents intended for complex workflows. However, their deployment as reliable AI workers in enterpris…