2 citations · 2 across the 16 of their papers we have counts for
5 papers · 1 filter
Break It Down, Pass It On: Cross-Task Skill Transfer in LLM Agents
Yiyang Feng, Biddut Sarker Bijoy, Niranjan Balasubramanian +1
Large language model (LLM) agents can induce skills from completed tasks and reuse them later to grow more capable with experience. In practice, induced skills may transfer unrelia…
Certificates without Electrons? Theory and Evidence on Impacts from AI-Driven Power Demand
Dana Golden, Aruna Balasubramanian, Niranjan Balasubramanian
Data centers now account for 4.4% of United States electricity demand, yet the grid-level effectiveness of the renewable energy certificates (RECs) and power purchase agreements (P…
AppWorld-UL: Benchmarking Diverse Agent-User Interactions for Tool-Use
Junzhi Chen, Harsh Trivedi, Jane Pan +4
Tool-use agents that address day-to-day digital tasks such as ordering groceries must not only operate applications, but also interact with the user, e.g., to ask clarification que…
Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation
Priscilla Kyei Danso, Mohammad Saqib Hasan, Niranjan Balasubramanian +1
Propositional Linear Temporal Logic (LTL) is a popular formalism for specifying desirable requirements and security and privacy policies for software, networks, and systems. Yet ex…
Teaching and Evaluating LLMs to Reason About Polymer Design Related Tasks
Dikshya Mohanty, Mohammad Saqib Hasan, Syed Mostofa Monsur +3
Research in AI4Science has shown promise in many science applications, including polymer design. However, current LLMs are ineffective in this problem space because: (i) most model…