5 citations · 10 across the 7 of their papers we have counts for
3 papers · 1 filter
LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess
Sai Kolasani, Maxim Saplin, Nicholas Crispino +5
We introduce LLM CHESS, an evaluation framework designed to probe the generalization of reasoning and instruction-following abilities in large language models (LLMs) through extend…
Optimizing Model Selection for Compound AI Systems
Lingjiao Chen, Jared Quincy Davis, Boris Hanin +4
Compound AI systems that combine multiple LLM calls, such as self-refine and multi-agent-debate, achieve strong performance on many AI tasks. We address a core question in optimizi…
Networks of Networks: Complexity Class Principles Applied to Compound AI Systems Design
Jared Quincy Davis, Boris Hanin, Lingjiao Chen +3
As practitioners seek to surpass the current reliability and quality frontier of monolithic models, Compound AI Systems consisting of many language model inference calls are increa…