1 citations · 3 across the 10 of their papers we have counts for
12 papers
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
Shaobo Wang, Xuan Ouyang, Tianyi Xu +9
As high-quality public text approaches exhaustion, a phenomenon known as the Data Wall, pre-training is shifting from more tokens to better tokens. However, existing methods either…
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…
ReViP: Mitigating False Completion in Vision-Language-Action Models with Vision-Proprioception Rebalance
Zhuohao Li, Yinghao Li, Jian-Jian Jiang +6
Vision-Language-Action (VLA) models have advanced robotic manipulation by combining vision, language, and proprioception to predict actions. However, previous methods fuse proprioc…
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…
AirCopBench: A Benchmark for Multi-drone Collaborative Embodied Perception and Reasoning
Jirong Zha, Yuxuan Fan, Tianyu Zhang +4
Multimodal Large Language Models (MLLMs) have shown promise in single-agent vision tasks, yet benchmarks for evaluating multi-agent collaborative perception remain scarce. This gap…
E-Pruner: Towards Efficient, Economical, and Effective Layer Pruning for Large Language Models
Tao Yuan, Haoli Bai, Yinfei Pan +5
With the increasing size of large language models, layer pruning has gained increased attention as a hardware-friendly approach for model compression. However, existing layer pruni…
Chronological Thinking in Full-Duplex Spoken Dialogue Language Models
Donghang Wu, Haoyang Zhang, Chen Chen +8
Recent advances in spoken dialogue language models (SDLMs) reflect growing interest in shifting from turn-based to full-duplex systems, where the models continuously perceive user…
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…
PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models
Shi Qiu, Shaoyang Guo, Zhuo-Yang Song +51
Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task oversimplification, data contamination, and flawed e…
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…
Creating a Cooperative AI Policymaking Platform through Open Source Collaboration
Aiden Lewington, Alekhya Vittalam, Anshumaan Singh +48
Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Curre…
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…