Search: “papers”

arXiv:2604.15929v1 Announce Type: new Abstract: The goal of multilingual speech technology is to facilitate seamless communication between individuals speaking different languages, creating the experi

arXiv:2604.15475v1 Announce Type: new Abstract: Deploying learned multi-robot models on heterogeneous robots remains challenging due to hardware heterogeneity, communication constraints, and the lack

arXiv:2412.04497v5 Announce Type: replace-cross Abstract: Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite the

arXiv:2603.11698v2 Announce Type: replace-cross Abstract: Text-to-video (T2V) generation models have made rapid progress in producing visually high-quality and temporally coherent videos. However, exi

arXiv:2604.16220v1 Announce Type: new Abstract: In computer vision and machine learning for geographic data, out-of-domain generalization is a pervasive challenge, arising from uneven global data cove

arXiv:2512.06987v2 Announce Type: replace Abstract: Accurately predicting experimentally realizable 3D molecular crystal structures from their 2D chemical graphs is a long-standing open challenge in c

arXiv:2604.15364v1 Announce Type: cross Abstract: Edge intelligence is constrained by the energy and latency costs of shuttling data through electronic memory hierarchies. Optical systems offer a fund

arXiv:2604.15558v1 Announce Type: new Abstract: Deliberative multi-agent systems allow agents to exchange messages and revise beliefs over time. While this interaction is meant to improve performance,

arXiv:2411.09355v3 Announce Type: replace-cross Abstract: We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially

arXiv:2604.15411v1 Announce Type: cross Abstract: The paradigm of agentic science requires AI systems to conduct robust reasoning and engage in long-horizon, autonomous exploration. However, current s

arXiv:2602.13088v2 Announce Type: replace-cross Abstract: The distinction between genuine grassroots activism and automated influence operations is collapsing. While contemporary policy debates priori

arXiv:2604.15464v1 Announce Type: cross Abstract: Large Language Model (LLM) deployment is increasingly shifting to cost-efficient accelerators like Google's Tensor Processing Units (TPUs), prioritizi

arXiv:2604.15736v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) excel at generic video understanding, their ability to support specialized, rule-grounded decision-maki

arXiv:2604.15621v1 Announce Type: cross Abstract: Adaptive Retrieval-Augmented Generation aims to mitigate the interference of extraneous noise by dynamically determining the necessity of retrieving s

arXiv:2604.15577v1 Announce Type: cross Abstract: Consider an auto-regressive model that produces outputs x (e.g., answers to questions, molecules) each of which can be summarized by an attribute vect

arXiv:2604.15890v1 Announce Type: new Abstract: Multi-UAV inspection missions require spare drones to replace active drones during recharging cycles. Existing fleet-sizing approaches often assume stea

arXiv:2604.15856v1 Announce Type: cross Abstract: Multimodal remote sensing data provide complementary information for semantic segmentation, but in real-world deployments, some modalities may be unav

arXiv:2604.16033v1 Announce Type: cross Abstract: Buildings account for approximately 40% of global energy consumption, and with the growing share of intermittent renewable energy sources, enabling de

arXiv:2503.05578v4 Announce Type: replace Abstract: Pose estimation-guided unseen object 6-DoF robotic manipulation is a key task in robotics. However, the scalability of current pose estimation metho

arXiv:2509.25300v4 Announce Type: replace-cross Abstract: While scaling laws for large language models (LLMs) during pre-training have been extensively studied, their behavior under reinforcement lear

arXiv:2604.16117v1 Announce Type: cross Abstract: Practice and extensive exercises are essential in programming education. Intelligent tutoring systems (ITSs) are a viable option to provide individual

arXiv:2602.11327v2 Announce Type: replace-cross Abstract: The rapid development of the AI agent communication protocols, including the Model Context Protocol (MCP), Agent2Agent (A2A), Agora, and Agent

arXiv:2308.10562v2 Announce Type: cross Abstract: The field of Computer Vision (CV) is increasingly shifting towards ``high-level'' visual sensemaking tasks, yet the exact nature of these tasks remain

arXiv:2604.15777v1 Announce Type: cross Abstract: Segmentation is a critical task in computational pathology, as it identifies areas affected by disease or abnormal growth and is essential for diagnos

arXiv:2604.15569v1 Announce Type: new Abstract: Manipulation policies deployed in uncontrolled real-world scenarios are faced with great in-category geometric diversity of everyday objects. In order t

arXiv:2504.16315v4 Announce Type: replace-cross Abstract: The complexity of Sign Language (SL) data processing brings many challenges. The current approach to recognition of SL signs aims to translate

arXiv:2604.16037v1 Announce Type: new Abstract: The widespread adoption of large language models (LLMs) has increased concerns about their robustness. Vulnerabilities in perturbations of tokenisation

arXiv:2604.15357v1 Announce Type: cross Abstract: Precise estimation of model inference latency is crucial for time-critical mobile edge applications, enabling devices to calculate latency margins aga

The AI industry insists they can manage the risks of superintelligence, but there are in fact zero widely agreed on or accepted solutions to the problem of how one could even control something vastly

arXiv:2604.16079v1 Announce Type: new Abstract: The success of deep generative models in generating high-quality and diverse samples is often attributed to particular architectures and large training

arXiv:2604.15370v1 Announce Type: cross Abstract: Graph adversarial attacks are usually produced from the two perspectives of topology/structure and node feature, both of them represent the paramount

arXiv:2604.15898v1 Announce Type: new Abstract: For around a decade, non-symbolic methods have been the option of choice when explaining complex machine learning (ML) models. Unfortunately, such metho

arXiv:2604.15705v1 Announce Type: new Abstract: Reinforcement Fine-Tuning (RFT) has established itself as a critical paradigm for the alignment of Multi-modal Large Language Models (MLLMs) with comple

arXiv:2511.00739v3 Announce Type: replace Abstract: Agentic AI serving converts monolithic LLM-based inference to autonomous problem-solvers that can plan, call tools, perform reasoning, and adapt on

arXiv:2604.15339v1 Announce Type: cross Abstract: Uncertainty, vagueness, and ambiguity are closely related and often confused concepts in human-robot interaction (HRI). In earlier studies, these conc

arXiv:2604.16119v1 Announce Type: new Abstract: Multivariate time series classification (MTSC) plays a crucial role in various domains, including biomedical signal analysis and motion monitoring. Howe

arXiv:2604.16084v1 Announce Type: cross Abstract: Traffic forecasting is a challenging spatio-temporal modeling task and a critical component of urban transportation management. Current studies mainly

arXiv:2604.15827v1 Announce Type: cross Abstract: Conventional information retrieval is concerned with identifying the relevance of texts for a given query. Yet, the conventional definition of relevan

arXiv:2604.16280v1 Announce Type: new Abstract: Explaining Machine Learning (ML) results in a transparent and user-friendly manner remains a challenging task of Explainable Artificial Intelligence (XA

arXiv:2604.15940v1 Announce Type: new Abstract: Fixed Radius Near Neighbor (FRNN) search is an alternative to the widely used k Nearest Neighbors (kNN) search. Unlike kNN, FRNN determines a label or a

arXiv:2604.15764v1 Announce Type: cross Abstract: Early-exit neural networks enable adaptive computation by allowing confident predictions to exit at intermediate layers, achieving 2-8imes inference s

Yann LeCun was right the entire time. And generative AI might be a dead end. For the last three years, the entire industry has been obsessed with building bigger LLMs. Trillions of parameters. Billion

Automated lint: 43 errors, 9 warnings, 3 info

LLM Artifacts Connected to @karpathy's LLM Knowledge base idea, I've been building out a fun way to generate dynamic artifacts from these knowledge bases with the goal of discovering and revealing mea

That didn't take long for a total U turn. First the Nvidia CEO boasted AI would take a vast number of jobs. But now that there's a huge backlash against AI, he cobbles together this cope - to try to p

A downside with using VLMs to parse PDFs is guaranteeing that the output text is *correct* and output in the correct reading order. 1️⃣ Text correctness: making sure that digits, words, sentences are