440 citations · 947 across the 43 of their papers we have counts for
45 papers
StarHarness: Evolving Harnesses with Stratified Search for Enterprise Environments
Esakkivel Esakkiraja, Denis Akhiyarov, Vikas Yadav +4
We present StarHarness, a framework for evolving environment-specific agent harnesses while keeping model weights fixed. The evolved harness can include prompt and task framing, to…
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…
Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics
Jishnu Sethumadhavan Nair, Patrice Bechard, Rishabh Maheshwary +14
World models enable agents to anticipate the effects of their actions by internalizing environment dynamics. In enterprise systems, however, these dynamics are often defined by ten…
MSPR: Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning
Valliappan Chidambaram Adaikkappan, David Meger, Sai Rajeswar +1
This paper investigates robust representation learning in offline goal-conditioned reinforcement learning (GCRL). Particularly in sparse reward scenarios, learning representations…
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…