7 citations · 29 across the 24 of their papers we have counts for
3 papers · 1 filter
MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning
Justin Chih-Yao Chen, Archiki Prasad, Swarnadeep Saha +2
Large Language Models' (LLM) reasoning can be improved using test-time aggregation strategies, i.e., generating multiple samples and voting among generated samples. While these imp…
System-1.x: Learning to Balance Fast and Slow Planning with Language Models
Swarnadeep Saha, Archiki Prasad, Justin Chih-Yao Chen +3
Language models can be used to solve long-horizon planning problems in two distinct modes: a fast 'System-1' mode, directly generating plans without any explicit search or backtrac…
MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
Justin Chih-Yao Chen, Swarnadeep Saha, Elias Stengel-Eskin +1
Multi-agent interactions between Large Language Model (LLM) agents have shown major improvements on diverse reasoning tasks. However, these involve long generations from multiple m…