Search: “models”

QA-MoE: Towards a Continuous Reliability Spectrum with Quality-Aware Mixture of Experts for Robust Multimodal Sentiment Analysis

arXiv:2604.05704v2 Announce Type: replace Abstract: Multimodal Sentiment Analysis (MSA) aims to infer human sentiment from textual, acoustic, and visual signals. In real-world scenarios, however, mult

applicationsarxiv-cs-ai

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Quantifying Explanation Consistency: The C-Score Metric for CAM-Based Explainability in Medical Image Classification

DGX agent

arXiv:2604.08502v1 Announce Type: new Abstract: Class Activation Mapping (CAM) methods are widely used to generate visual explanations for deep learning classifiers in medical imaging. However, existi

local-aiarxiv-cs-cv

10 Apr 2026

RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs

arXiv:2604.07765v1 Announce Type: new Abstract: Earth Observation (EO) systems are essentially designed to support domain experts who often express their requirements through vague natural language ra

agentsarxiv-cs-cv

Rotation Equivariant Convolutions in Deformable Registration of Brain MRI

arXiv:2604.08034v1 Announce Type: new Abstract: Image registration is a fundamental task that aligns anatomical structures between images. While CNNs perform well, they lack rotation equivariance - a

safetyarxiv-cs-cv

Self-Discovered Intention-aware Transformer for Multi-modal Vehicle Trajectory Prediction

arXiv:2604.07126v1 Announce Type: cross Abstract: Predicting vehicle trajectories plays an important role in autonomous driving and ITS applications. Although multiple deep learning algorithms are dev

Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications

arXiv:2603.13970v2 Announce Type: replace Abstract: In High Energy Physics, as in many other fields of science, the application of machine learning techniques has been crucial in advancing our underst

SonoSelect: Efficient Ultrasound Perception via Active Probe Exploration

arXiv:2604.05933v3 Announce Type: replace Abstract: Ultrasound perception typically requires multiple scan views through probe movement to reduce diagnostic ambiguity, mitigate acoustic occlusions, an

Sparse-Aware Neural Networks for Nonlinear Functionals: Mitigating the Exponential Dependence on Dimension

arXiv:2604.06774v1 Announce Type: cross Abstract: Deep neural networks have emerged as powerful tools for learning operators defined over infinite-dimensional function spaces. However, existing theori

Splits! Flexible Sociocultural Linguistic Investigation at Scale

arXiv:2504.04640v3 Announce Type: replace Abstract: Variation in language use, shaped by speakers' sociocultural background and specific context of use, offers a rich lens into cultural perspectives,

researcharxiv-cs-cl

Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation

arXiv:2604.07321v1 Announce Type: cross Abstract: Propositional Linear Temporal Logic (LTL) is a popular formalism for specifying desirable requirements and security and privacy policies for software,

Tarot-SAM3: Training-free SAM3 for Any Referring Expression Segmentation

arXiv:2604.07916v1 Announce Type: new Abstract: Referring Expression Segmentation (RES) aims to segment image regions described by natural-language expressions, serving as a bridge between vision and

The Rhetoric of Machine Learning

arXiv:2604.06754v1 Announce Type: new Abstract: I examine the technology of machine learning from the perspective of rhetoric, which is simply the art of persuasion. Rather than being a neutral and 'o

The Sustainability Gap in Robotics: A Large-Scale Survey of Sustainability Awareness in 50,000 Research Articles

arXiv:2604.07921v1 Announce Type: new Abstract: We present a large-scale survey of sustainability communication and motivation in robotics research. Our analysis covers nearly 50,000 open-access paper

safetyarxiv-cs-ro

The Theorems of Dr. David Blackwell and Their Contributions to Artificial Intelligence

arXiv:2604.06621v1 Announce Type: cross Abstract: Dr. David Blackwell was a mathematician and statistician of the first rank, whose contributions to statistical theory, game theory, and decision theor

safetyarxiv-cs-lg

The Unreasonable Effectiveness of Data for Recommender Systems

arXiv:2604.06420v2 Announce Type: cross Abstract: In recommender systems, collecting, storing, and processing large-scale interaction data is increasingly costly in terms of time, energy, and computat

Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach

arXiv:2602.18377v3 Announce Type: replace-cross Abstract: Quantum reservoir computers (QRCs) have emerged as a promising approach to quantum machine learning, since they utilize the natural dynamics o

When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction

arXiv:2604.06558v1 Announce Type: new Abstract: We present the first systematic study of when target context helps molecular property prediction, evaluating context conditioning across 10 diverse prot

A Decision-Aware Evaluation Protocol for Uncertainty in Medical Image Segmentation

arXiv:2610.21616v1 Announce Type: new Abstract: Medical segmentation uncertainty is often evaluated with calibration error or pixel-level error-detection scores, but these metrics do not show whether

safetyarxiv-cs-cv

A large-scale climate-aware satellite image dataset for domain adaptive land-cover semantic segmentation

arXiv:2610.21238v1 Announce Type: new Abstract: A few well-annotated datasets for land-cover semantic segmentation have recently been introduced to advance the field of earth observation technologies.

Affordance-Aware Interactive Decision-Making and Execution for Ambiguous Instructions

arXiv:2602.05273v2 Announce Type: replace Abstract: Enabling robots to explore and act in unfamiliar environments under ambiguous human instructions by interactively identifying task-relevant objects

applicationsarxiv-cs-ro

Agent Status Protocol (ASP): A Lightweight Specification for State Reporting in Multi-Agent Systems

arXiv:2610.21538v1 Announce Type: new Abstract: The Agent Status Protocol (ASP) defines a lightweight way for heterogeneous AI agents to report their operational state to a status server, and for obse

AI-Driven Disaster Response and Displacement Monitoring

arXiv:2610.21482v1 Announce Type: new Abstract: ARTIFICIAL INTELLIGENCE (AI) has demonstrated its potential across a wide range of humanitarian tasks, offering scalable and data-driven solutions to so

Hardware

ANEForge: Python for direct computation on the Apple Neural Engine

arXiv:2606.17090v2 Announce Type: replace-cross Abstract: ANEForge is a Python package that programs the Apple Neural Engine (ANE), the fixed-function neural accelerator on every recent Apple device,

hardwarearxiv-cs-ai

Believed but Not Said: Measuring Hidden Belief Collapse in Multi-Agent LLM Discussions

arXiv:2610.22138v1 Announce Type: new Abstract: LLM systems increasingly rely on groups of agents that discuss, critique, and check one another, assuming that peers will catch individual errors. We te

Tutorials

Beyond Fixed Acquisition Functions: Temporal Difference Active Learning for Perturbation Discovery

arXiv:2610.22122v1 Announce Type: new Abstract: Genetic and drug perturbation screens are important tools for elucidating disease mechanisms and validating therapeutic targets, but experimental costs

tutorialsarxiv-cs-lg

Beyond Retrieval Failure: Understanding Why LLMs Miss Evidence in Multi-Hop RAG

arXiv:2610.21184v1 Announce Type: new Abstract: Multi-hop retrieval-augmented generation (RAG) requires an agent to retrieve evidence for a sequence of dependent sub-questions. When a wrong answer lac

agentsarxiv-cs-cl

Local Ai

Blame Errant Words, Not the Canvas: Defect-Aware Spatial Credit Assignment for Visual Text Generation

arXiv:2610.20794v1 Announce Type: new Abstract: Recent reinforcement learning approaches have improved visual text generation, yet generated images still suffer from incorrect wording and malformed gl

local-aiarxiv-cs-cv

BOLT: Universal Classifier Training via a Bayes-Error Upper Bound

arXiv:2501.07754v2 Announce Type: replace-cross Abstract: This work introduces a novel approach to compute a universal upper bound on the Bayes error rate (BER) from classifier-output samples, which s

applicationsarxiv-cs-cv

CARA: Causally Guided Retrieval Agent for Question Answering

arXiv:2610.22017v1 Announce Type: new Abstract: Retrieval-augmented generation over text-rich knowledge graphs requires identifying evidence that contributes to answering a question, rather than merel

CF-AVSS: A Coarse-to-Fine Audio-Visual Speech Separation Framework with Target-Speaker Refinement and Post-Fusion for Real-World AVSE Challenge

arXiv:2610.21773v1 Announce Type: cross Abstract: Audio-visual speech enhancement (AVSE) leverages visual cues to recover target speech from mixtures corrupted by reverberation, noise, and overlapping

applicationsarxiv-cs-ai

Local Ai

ChronoSheaf: Joint Spatio-Temporal Spectral Filtering on Cellular Sheaves

arXiv:2610.21958v1 Announce Type: new Abstract: Sheaf neural networks generalize graph neural networks by assigning each edge a learned linear restriction map that specifies how the local representati

local-aiarxiv-cs-lg

Close Enough is Nowhere Near: Fidelity-Consumability Decoupling in KV Caches

arXiv:2610.22016v1 Announce Type: new Abstract: Multi-agent LLM systems communicate in text, which is lossy and wasteful: the sender throws away the reading it already did. A growing literature instea

agentsarxiv-cs-lg

Coordination-Free Workload Regularization for Variable-Cost Distributed Training

arXiv:2610.21162v1 Announce Type: cross Abstract: Synchronous data-parallel training usually assigns every rank the same number of records, even when record costs vary by orders of magnitude. For vari

safetyarxiv-cs-lg

CoViG: Coarsened Vision GNN for Image Classification

arXiv:2610.21321v1 Announce Type: new Abstract: Although Graph Neural Networks are widely used in various domains, they remained mostly unexplored in computer vision. Convolutional Neural Networks and

Cross-subject decoding of imagined speech from scalp EEG: a leakage-controlled evaluation on three public corpora

arXiv:2610.20954v1 Announce Type: cross Abstract: Objective. A decoder of imagined speech that works for a new user without calibration would make a non-invasive speech interface practical. We tested

safetyarxiv-cs-lg

Decentralized LLM Workflows via Sequential Auctions

arXiv:2610.22201v1 Announce Type: cross Abstract: We present a scalable framework for solving multi-step tasks through a decentralized market of self-interested agents. Prior theoretical work demonstr

safetyarxiv-cs-ai

Dense4D: Pixel-Level 4D Human Correspondence

arXiv:2610.22325v1 Announce Type: new Abstract: Reconstructing human motion in 4D requires identifying the same surface points through articulation, deformation and changes in visibility. We introduce

Diviner: Agentic RCA with Human-Governed Adaptation for Large-Scale Infrastructure

arXiv:2610.21281v1 Announce Type: new Abstract: Root-cause analysis (RCA) in large-scale distributed systems is challenging because a single symptom can cross service, data, configuration, compute, an

Local Ai

DLOSAC: Joint Spatial-Geometric Image Estimation via Delaunay-Guided Local Optimization RANSAC

arXiv:2610.21215v1 Announce Type: new Abstract: Reliable image geometric estimation from noisy matching points is typically addressed using RANSAC, often combined with local optimization to refine inl

local-aiarxiv-cs-cv

Documenting Trofinetide Treatment Phenotypes in Rett Syndrome with a Dual-LLM Consensus Pipeline

arXiv:2610.22062v1 Announce Type: cross Abstract: Objective: Trofinetide, approved in 2023 as the first Rett syndrome treatment, lacks scalable real-world monitoring because chart review is labor-inte

applicationsarxiv-cs-cl

Does Morphological Correctness Matter for Tokenization? A Scrambled Control Study in Tagalog

arXiv:2610.20859v1 Announce Type: new Abstract: Typology-aware tokenizers are motivated by the claim that segmentation which respects morpheme boundaries preserves information that frequency-driven se

researcharxiv-cs-cl

Does On-Policy Distillation Need to Complete Every Rollout?

arXiv:2610.21337v1 Announce Type: cross Abstract: On-policy distillation (OPD) effectively transfers capabilities from a teacher to a student through feedback on student-generated rollouts. However, g

safetyarxiv-cs-ai

Edit4D: Editable 4D Scene Generation with Textual Control

arXiv:2610.21668v1 Announce Type: new Abstract: We introduce Edit4D, an editable text-to-4D scene generation framework that constructs 4D scenes from separate background and dynamic character represen

Efficient Agnostic Learning of Univariate Densities Under Local Differential Privacy

arXiv:2610.21033v1 Announce Type: cross Abstract: We propose a general framework for non-interactive locally differentially private (LDP) learning of structured univariate distributions that can be ap

FedSumUp: User-Auditable Privacy-Aware Representation Sharing for Resource-Constrained Federated Intelligence

arXiv:2610.21194v1 Announce Type: cross Abstract: Existing federated data condensation methods face privacy risks, as uploaded synthetic data may preserve sensitive information and remain vulnerable t

Finite-Time Guarantees for Constrained Reinforcement Learning under Partial Observability

arXiv:2610.21548v1 Announce Type: new Abstract: We study reinforcement learning in constrained partially observable Markov decision processes (CPOMDPs), where an agent maximizes reward subject to a co

agentsarxiv-cs-lg

Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE

arXiv:2603.11611v2 Announce Type: replace-cross Abstract: Rotary Positional Embedding (RoPE) is widely used in transformers to encode relative positional information, yet the effect of applying RoPE t

researcharxiv-cs-cl

From Documents to Spans: Span-Centric Learning for LLM-based Explainable Medical Coding

arXiv:2603.15270v3 Announce Type: replace-cross Abstract: Medical coding, which assigns standardized ICD codes to clinical documents, is a fundamental yet challenging task in modern healthcare. It req

safetyarxiv-cs-ai