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arXiv:2411.15955v4 Announce Type: replace Abstract: Inter-symbol interference (ISI) limits reliability in diffusion-based molecular communication (MC) channels. We propose RLIM, a family of run-length-limited (RLL) codes...
arXiv:2412.01256v3 Announce Type: replace Abstract: The emergence of vision-language foundation models, such as CLIP, has revolutionized image-text representation, enabling a broad range of applications via...
arXiv:2412.07477v4 Announce Type: replace Abstract: In earthwork and construction, excavators often encounter large rocks mixed with various soil conditions, requiring skilled operators. This paper presents...
arXiv:2412.16167v2 Announce Type: replace Abstract: Multi-connectivity involves dynamic cluster formation among distributed access points (APs) and coordinated resource allocation from these APs, highlighting the need...
arXiv:2412.17543v3 Announce Type: replace Abstract: We deal with accelerating the solution of a sequence of large linear systems solved by preconditioned conjugate gradient method (PCG)....
arXiv:2412.20846v2 Announce Type: replace Abstract: Large language models (LLMs) have shown promise as parametric knowledge bases, but often underperform on question answering (QA) tasks due...
arXiv:2501.01921v2 Announce Type: replace Abstract: While knowledge distillation has shown success in various audio tasks, its application to environmental sound classification often overlooks essential low-level...
arXiv:2501.09718v2 Announce Type: replace Abstract: Low-Light Image Enhancement (LLIE) is a key task in computational photography and imaging. The problem of enhancing images captured during...
arXiv:2501.14277v3 Announce Type: replace Abstract: We present Dense-SfM, a novel Structure from Motion (SfM) framework designed for dense and accurate 3D reconstruction from multi-view images....
arXiv:2501.16033v2 Announce Type: replace Abstract: Understanding and engaging with privacy policies is crucial for online privacy, yet these documents remain notoriously complex and difficult to...
arXiv:2501.19180v2 Announce Type: replace Abstract: Large language models (LLMs) are vital for a wide range of applications yet remain susceptible to jailbreak threats, which could...
arXiv:2502.01777v3 Announce Type: replace Abstract: Modern deep learning models often achieve high overall performance, but consistently fail on specific subgroups. Group distributionally robust optimization (group...
arXiv:2502.05739v2 Announce Type: replace Abstract: Large Language Models for Code (LLMs4Code) have achieved strong performance in code generation, but recent studies reveal that they may...
arXiv:2502.06545v5 Announce Type: replace Abstract: We study the problem of preconditioning in sequential prediction. From the theoretical lens of linear dynamical systems, we show that...
arXiv:2502.08005v5 Announce Type: replace Abstract: Score-based distillation methods (e.g., variational score distillation) train one-step diffusion models by first pre-training a teacher score model and then...
arXiv:2502.08792v3 Announce Type: replace Abstract: We study auction design when a seller relies on machine-learning predictions of bidders' valuations that may be unreliable. Motivated by...
arXiv:2502.09667v4 Announce Type: replace Abstract: We introduce k-NLPmeans and k-LLMmeans, text-clustering variants of k-means that periodically replace numeric centroids with textual summaries. The key idea,...
arXiv:2502.10138v4 Announce Type: replace Abstract: We study the reinforcement learning (RL) problem in a constrained Markov decision process (CMDP), where an agent explores the environment...
arXiv:2502.11068v2 Announce Type: replace Abstract: Anchors is a popular local model-agnostic explanation technique whose applicability is limited by its computational inefficiency. To address this limitation,...
arXiv:2502.13369v3 Announce Type: replace Abstract: The ability to generate SPARQL queries from natural language questions is crucial for ensuring efficient and accurate retrieval of structured...
arXiv:2502.16744v2 Announce Type: replace Abstract: Projection-based algorithms for Constrained Online Convex Optimization (COCO) achieve optimal $\mathcal{O}(T^{1/2})$ regret guarantees but face scalability challenges due to the...
arXiv:2502.17629v4 Announce Type: replace Abstract: The palette sparsification theorem (PST) of Assadi, Chen, and Khanna (SODA 2019) states that in every graph $G$ with maximum...
arXiv:2503.00344v3 Announce Type: replace Abstract: This paper presents an algorithm to improve state estimation for legged robots. Among existing model-based state estimation methods for legged...
arXiv:2503.01544v2 Announce Type: replace Abstract: It is well understood that different neural network architectures are suited to different tasks, but is there always a single...