1 citations · 3 across the 10 of their papers we have counts for
5 papers · 1 filter
Dynamic Large Concept Models: Latent Reasoning in an Adaptive Semantic Space
Xingwei Qu, Shaowen Wang, Zihao Huang +16
Large Language Models (LLMs) apply uniform computation to all tokens, despite language exhibiting highly non-uniform information density. This token-uniform regime wastes capacity…
Majority of the Bests: Improving Best-of-N via Bootstrapping
Amin Rakhsha, Kanika Madan, Tianyu Zhang +2
Sampling multiple outputs from a Large Language Model (LLM) and selecting the most frequent (Self-consistency) or highest-scoring (Best-of-N) candidate is a popular approach to ach…
Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
Marco Jiralerspong, Esther Derman, Danilo Vucetic +5
A major bottleneck in scientific discovery consists of narrowing an exponentially large set of objects, such as proteins or molecules, to a small set of promising candidates with d…
Aligning Constraint Generation with Design Intent in Parametric CAD
Evan Casey, Tianyu Zhang, Shu Ishida +6
We adapt alignment techniques from reasoning LLMs to the task of generating engineering sketch constraints found in computer-aided design (CAD) models. Engineering sketches consist…
Advantage Alignment Algorithms
Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans +4
Artificially intelligent agents are increasingly being integrated into human decision-making: from large language model (LLM) assistants to autonomous vehicles. These systems often…