The Musical Metaverse (MM) enables geographically distributed musicians, audiences, sound engineers, and AI agents to interact through synchronized audio, visual, kinematic, and haptic streams, imposing latency, synchronization, bandwidth, and scalability requirements that are difficult to satisfy with conventional bit...
Ali Al Housseini, Jaime Llorca, Cristina Rottondi et al.· 0 citations
Large language model (LLM) assistants increasingly advise backers on which crowdfunding campaigns to support. LLMs have known race and gender problems, and it is unsettled whether they reproduce, erase, or reverse the discrimination documented in entrepreneurial finance. We ask when, and through which decision process,...
Mirza Samad Ahmed Baig, Syeda Anshrah Gillani· 0 citations
Long-context inference is bound by the KV cache, which 2-bit codes could shrink about sixfold if their error stays in check. The usual remedy rotates keys before quantizing, assuming rotation always helps. However, we observe that it does not: rotation flattens a spiky piece of a key but can give a flat one a new peak,...
Kunming Shao, Xijie Huang, Jierun Chen et al.· 0 citations
Enterprises increasingly want LLM agents to automate standard operating procedures over their software stacks -- mapping each step of a procedure to the right call among thousands of internal APIs, without hand-authored step-to-API mappings. The core difficulty is API selection at scale: choosing and composing the corr...
Rongzhe Wei, Ge Shi, Min Cheng et al.· 0 citations
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Assistive systems typically tell users everything, often spending time and attention on what a user already knows, leaving less for what happens next. People, on the other hand, leave out what they expect the listener can supply. Can people use their prior knowledge to understand an incomplete message when the speaker...
Large Language Bayes (LLB) transforms a natural language problem description into a collection of candidate probabilistic programs and performs inference within each model, combining their predictions using Bayesian model averaging. While this provides a flexible framework for probabilistic inference without manual mod...
Anant Bhide, Akarsh Gupta, Edmond Cunningham et al.· 0 citations
Protein-protein interactions underpin nearly all biological processes. Yet, designing proteins with desired interactions remains challenging due to the structural complexity governing molecular recognition. This study views protein design as a search optimization problem over a combinatorial sequence space under expens...
Fang Wu, Hong-Bin Lin, Bing-Chen Duan et al.· 0 citations
Multi-teacher on-policy distillation consolidates expert capabilities by supervising student-generated trajectories, whereas task arithmetic offers a training-free alternative through linear parameter combinations. We view the linear combination of student and expert parameters as a single differentiable model and prop...
Sinuo Wang, Jiacheng Lu, Zeyu Zhang et al.· 0 citations
Small language models (<=9B parameters) can support local medical question answering (QA) while reducing privacy and latency concerns, but effective fine-tuning remains challenging. This paper compares two chain-of-thought (CoT) supervised fine-tuning methods: Uniform-across-Sequence (UaS), which applies equal loss wei...
Le Zhou, Xiao Luo, Chinmay Chandra et al.· 0 citations
Autonomous vehicles require robust perception systems to operate safely under diverse environmental conditions. While cameras provide high-resolution visual data, their performance significantly degrades in low-light and adverse weather. High Definition (HD) radar offers superior reliability and angular resolution unde...
This work investigates whether open-weight models can generate less verbose reasoning by changing the form of their own earlier thoughts, without retraining, and identifies reasoning history as one way to reduce future reasoning-token use and motivate model-specific compaction policies evaluated for both efficiency and...
A. Hristov· Proceedings of the Second Wo...· 0 citations
Simulation benchmarks are the standard way to compare robot policies, but each benchmark brings its own evaluator, observation layout, and action convention, and evaluation is slow: 500 RoboTwin Easy episodes with one simulator and one model on one GPU take 359.7 minutes. Profiling the official StarVLA evaluator shows...
Deng-Ke Wu, Yifan Jin, Yida Yang et al.· 0 citations
