2 citations · 3 across the 12 of their papers we have counts for
4 papers · 1 filter
DCEmbed: Scalable Optimization over Neural Surrogates
Akshay Sreekumar, Nicolas Christianson, Priya L. Donti +2
Neural surrogates can accelerate large-scale optimization by replacing expensive or intractable model components with efficient learned approximations, but solving the resulting em…
Compositional Reasoning in Language Models under Reinforcement Learning Post-Training
Yu He, Yingxi Li, Yifei Wang +1
Compositional reasoning is critical for real-world problem solving: since training data is necessarily limited, models must generalize by composing learned skills in new ways. Whil…
FLARE: Verifying MILP Reformulations with LLM-Based Theorem Proving
Henry Robbins, Connor Lawless, Madeleine Udell +1
Mixed-Integer Linear Programming (MILP) is a fundamental tool for combinatorial optimization with extensive real-world applications. A central challenge is designing computationall…
Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking
Nikil Roashan Selvam, Jay Baxter, Sophie Hilgard +4
Crowdsourced fact-checking systems have been adopted by major social media companies such as X, Meta, TikTok and Google with the aim of combating misleading information at scale wi…