1 citations · 1 across the 4 of their papers we have counts for
4 papers
AllocBench: Measuring Online Tool Allocation Capability in LLM Agents
Daniel Wang, Andrew Xu
Creating a reusable tool is an investment: an agent pays a fixed cost now in exchange for the potential of future reuse. Therefore, a user should prefer an agent that creates a sma…
Lomekwi: Resource-Bounded Tool Discovery in LLM Agents
Roshan Klein-Seetharaman, Daniel Wang, Andrew Xu
Existing tool-use benchmarks report a single success rate for complex, multistep tasks. Inspired by ideas from cognitive science, we distinguish tool use from tool discovery and de…
RankLLM: A Python Package for Reranking with LLMs
Sahel Sharifymoghaddam, Ronak Pradeep, Andre Slavescu +7
The adoption of large language models (LLMs) as rerankers in multi-stage retrieval systems has gained significant traction in academia and industry. These models refine a candidate…
Centralized Selection with Preferences in the Presence of Biases
L. Elisa Celis, Amit Kumar, Nisheeth K. Vishnoi +1
This paper considers the scenario in which there are multiple institutions, each with a limited capacity for candidates, and candidates, each with preferences over the institutions…