Search: “papers”

arXiv:2605.01315v1 Announce Type: new Abstract: This paper investigates sentiment classification of Steam game reviews using an attention-based Bidirectional Long Short-Term Memory (BiLSTM) model. Usi

arXiv:2605.01036v1 Announce Type: new Abstract: This paper tackles the problem of physics-aware human motion synthesis in a dynamic scene. Unlike existing works which mainly tend to generate physicall

arXiv:2605.02052v1 Announce Type: new Abstract: This discussion paper reflects on how quantitative approaches to historical linguistics interact with dataset properties. Drawing on two worked examples

arXiv:2605.02212v1 Announce Type: new Abstract: This paper presents a comprehensive review of the NITRE 2026 Efficient Low Light Image Enhancement (E-LLIE) Challenge, highlighting the proposed solutio

arXiv:2603.26013v2 Announce Type: replace Abstract: Multilingual NLP is often treated as a route to global inclusion, but linguistic coverage and cultural competence frequently diverge. This paper syn

arXiv:2605.02487v1 Announce Type: new Abstract: This paper addresses the problem of mobile grasping in dynamic, unknown environments where a robot must operate under a limited field-of-view. The funda

arXiv:2604.26977v1 Announce Type: cross Abstract: In response to a concern raised by Horty, this paper develops a two-tiered, preference-based semantic framework for modeling defeasible conditional ob

arXiv:2604.28158v1 Announce Type: new Abstract: Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of meth

arXiv:2604.26835v1 Announce Type: cross Abstract: We introduce HalluCiteChecker, a toolkit for detecting and verifying hallucinated citations in scientific papers. While AI assistant technologies have

arXiv:2604.25267v1 Announce Type: new Abstract: This paper addresses the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem involving one unmanned ground vehicle (UGV) assisted by one or more u

arXiv:2604.25384v1 Announce Type: new Abstract: This paper presents a methodology for transforming raw Wikimedia dumps into quality textual corpora for seven South Slavic languages. The work is divide

arXiv:2602.17547v3 Announce Type: replace Abstract: This paper introduces KLong, an open-source LLM agent trained to solve extremely long-horizon tasks. The principle is to first cold-start the model

arXiv:2604.23733v1 Announce Type: new Abstract: Asking inquisitive questions while reading, and looking for their answers, is an important part in human discourse comprehension, curiosity, and creativ

arXiv:2604.04353v2 Announce Type: replace-cross Abstract: Although HCI research papers offer valuable design insights, designers often struggle to apply them in design workflows due to difficulties in

arXiv:2602.21954v2 Announce Type: replace-cross Abstract: In Part I of this companion paper series, we introduced SWIFTraj, a new open-source vehicle trajectory dataset collected using a unmanned aeri

arXiv:2604.22834v1 Announce Type: new Abstract: This paper presents webmcu-vision-web, a single-file, zero-install browser application for end-to-end TinyML vision model training and deployment on the

arXiv:2604.21043v1 Announce Type: cross Abstract: This paper examines the strategic use of language in contemporary artificial intelligence (AI) discourse, focusing on the widespread adoption of metap

arXiv:2604.20868v1 Announce Type: cross Abstract: In this paper, I evaluate the risks of an AI criminal mastermind, an AI agent capable of planning, coordinating, and committing a crime through the on

arXiv:2604.20799v1 Announce Type: new Abstract: This paper presents a framework for mapping unknown scalar fields using a sensor-equipped autonomous robot operating in unsafe environments. The unsafe

arXiv:2604.19800v1 Announce Type: cross Abstract: This paper presents a detailed study of how graph neural networks can be used on edge intelligent meters in a microgrid to forecast photovoltaic power

arXiv:2308.00513v2 Announce Type: replace Abstract: This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide r

arXiv:2604.19645v1 Announce Type: new Abstract: An earlier paper (Hong, Potteiger, and Zapata 2026) established that an unoptimized GPT 4.1 prompt predicts fan-reported experience ratings within one p

arXiv:2507.12182v4 Announce Type: replace-cross Abstract: The paper is concerned with deformed Wigner random matrices. These matrices are closely related to Deep Neural Networks (DNNs): weight matrice

arXiv:2604.16865v1 Announce Type: cross Abstract: In this paper, we consider the problem of extraction of most informative features from time series that are regarded as observed values of stochastic

arXiv:2411.06812v2 Announce Type: replace-cross Abstract: This paper introduces the concept of ``generative midtended cognition'', exploring the integration of generative AI with human cognition. The

arXiv:2604.16949v1 Announce Type: new Abstract: The paper considers the computation of L1 regularization paths in a state space setting, which includes L1 regularized Kalman smoothing, linear SVM, LAS

arXiv:2604.17669v1 Announce Type: new Abstract: This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final result

arXiv:2507.16727v3 Announce Type: replace Abstract: Improving the reliability of large language models (LLMs) is critical for deploying them in real-world scenarios. In this paper, we propose extbf{De

arXiv:2604.14828v1 Announce Type: new Abstract: Educational assistants should spend more computation only when the task needs it. This paper rewrites our earlier draft around the system that was actua

arXiv:2505.19662v3 Announce Type: replace-cross Abstract: This paper introduces FieldWorkArena, a benchmark for agentic AI targeting real-world field work. With the recent increase in demand for agent

arXiv:2604.13345v1 Announce Type: new Abstract: The paper presents design and prototype implementation of an edge based object detection system within the new paradigm of AI agents orchestration. It g

arXiv:2604.12746v1 Announce Type: new Abstract: Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detec

arXiv:2604.09793v1 Announce Type: cross Abstract: Scientific breakthroughs often emerge from synthesizing prior ideas into novel contributions. While language models (LMs) show promise in scientific d

arXiv:2604.11261v1 Announce Type: new Abstract: This paper introduces AI as a Research Object (AI-RO), a paradigm for governing the use of generative AI in scientific research. Instead of debating whe

arXiv:2510.18976v2 Announce Type: replace Abstract: In this paper we describe Ninja Codes, neurally generated fiducial markers that can be made to naturally blend into various real-world environments.

arXiv:2604.09418v1 Announce Type: new Abstract: This paper studies Automated Instruction Revision (AIR), a rule-induction-based method for adapting large language models (LLMs) to downstream tasks usi

arXiv:2610.17312v1 Announce Type: new Abstract: This paper proposes a method for constructing a neural network that achieves perfect classification of all samples in a given training set, without taki

arXiv:2508.06313v2 Announce Type: replace Abstract: This paper presents a unified system-level modeling and control framework for an all-electric heavy-duty robotic manipulator (HDRM) driven by electr

arXiv:2610.18594v1 Announce Type: cross Abstract: This paper proposes an Autonomous Cyber Operations (ACO) gym, a unified framework integrating high-fidelity network emulation, realistic user behaviou

arXiv:2610.14856v1 Announce Type: new Abstract: This paper studies the problem of recovering motion from monocular video, even when the target skeleton topology differs from the subject observed in th

arXiv:2606.17192v2 Announce Type: replace Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimi

arXiv:2601.18313v2 Announce Type: replace-cross Abstract: This paper proposes a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications

arXiv:2610.15126v1 Announce Type: cross Abstract: Decentralized learning must balance collaboration with personalization across heterogeneous agents. This paper studies when cooperation can support st

arXiv:2610.14296v1 Announce Type: cross Abstract: High benchmark scores in learning-based vulnerability detection mask severe degradation under distribution shifts. This paper demonstrates that calibr

arXiv:2610.15996v1 Announce Type: new Abstract: In this paper, we propose the Dissipative Lagrangian Neural Network (dLNN), a continuous-time system identification technique that separately learns the

arXiv:2610.16142v1 Announce Type: cross Abstract: This paper develops a unified framework for distributional regression with arbitrary response variables. Rather than relying on scalar thresholds or E