Search: “framework”

A HamNoSys-Guided Dataset and Baselines for Fine-Grained Isolated Handshape Recognition in Sign Language

arXiv:2608.10588v1 Announce Type: cross Abstract: Purpose: Fine-grained handshape recognition supports computational sign-language transcription, recognition, and translation, but broad, phonetically

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes

DGX agent

arXiv:2608.10470v1 Announce Type: new Abstract: Fair representation learning with a continuous sensitive attribute S requires a representation Z that is statistically independent of S. Existing criter

safetyarxiv-cs-lg

12 Aug 2026

A Neural Network Based Teleoperation for Remote Controlled Vehicles

arXiv:2608.10367v1 Announce Type: new Abstract: Direct teleoperation of vehicles faces critical technical bottlenecks: communication latency and the operator's inability to physically perceive unmodel

safetyarxiv-cs-ro

APCReg: Anatomical-Prior-Guided Coarse-to-Fine CBCT--IOS Registration via Multi-View Projection and Reliability-Controlled Residual Correction

arXiv:2608.09993v1 Announce Type: cross Abstract: Registration between cone-beam computed tomography (CBCT) and intraoral scans (IOS) is essential for patient-specific surgical planning. However, disp

safetyarxiv-cs-cv

Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantization

arXiv:2602.02035v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significant

Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift

arXiv:2505.02257v2 Announce Type: replace-cross Abstract: In regions lacking medically certified causes of death, verbal autopsy (VA) is a widely used tool to ascertain the cause of death through inte

Beyond Decision Boundaries: Relational Geometry Attacks on Contrastive Embedding Manifolds

arXiv:2608.10237v1 Announce Type: new Abstract: Contrastive learning and Siamese embedding models have become the foundation of modern verification systems, where decisions are governed not by discret

Beyond Detection Accuracy: Measuring Explanation Cost, Stability, and Utility for Resource-Aware IoT Intrusion Detection

arXiv:2608.10349v1 Announce Type: cross Abstract: Machine-learning intrusion-detection studies commonly emphasize predictive accuracy while treating explanation generation as a computationally free po

BREAD: Baseline-Referenced Explanations for Anomaly Diagnosis

arXiv:2608.10587v1 Announce Type: new Abstract: Artificial Intelligence (AI)-based prospective anomaly detection methods are increasingly deployed in high-dimensional and nonlinear settings. Among the

Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?

arXiv:2603.02462v2 Announce Type: replace-cross Abstract: A key challenge in developing unified neural solvers for combinatorial optimization (CO) is the efficient generalization of models from a give

ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models

arXiv:2608.10120v1 Announce Type: new Abstract: Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typicall

Closing a 17-Year Gap: Algorithmic Detection and Empirical Prevalence of Rank Reversal in Multi-Criteria Decision Analysis

arXiv:2508.00129v2 Announce Type: replace Abstract: Rank Reversal, where the relative order of alternatives changes in ways that violate axioms of rational decision-making, is a well-documented threat

applicationsarxiv-cs-ai

Local Ai

Conversational Orchestration for Organic 6G

arXiv:2608.10714v1 Announce Type: cross Abstract: The Organic 6G vision of a network of networks spanning an edge-cloud continuum complemented by non-terrestrial resources requires, to realize its pro

local-aiarxiv-cs-ai

Deep Learning-Based Statistical Downscaling of Sea Surface Temperature Using a Residual Corrective Neural Network

arXiv:2608.10022v1 Announce Type: cross Abstract: The large-scale oceanic and atmospheric forecasts provided by global climate models typically lack sufficient resolution to accurately capture the res

Delays in Spiking Neural Networks: A State Space Model Approach

arXiv:2512.01906v3 Announce Type: replace Abstract: Spiking neural networks (SNNs) are biologically inspired, event-driven models suited for temporal data processing and energy-efficient neuromorphic

Demystifying Adversarial Robustness in Diffusion Models: Compression, Randomness, and Geometry

arXiv:2505.22839v2 Announce Type: replace-cross Abstract: Recent studies suggest that diffusion models significantly improve the empirical adversarial robustness of deep neural network models. While i

Deployment Is Not Destiny: Robot Recomposition in the Field with Unseen Software, Hardware, and Compute Payloads

arXiv:2608.11063v1 Announce Type: new Abstract: The tight coupling of subsystems in most robots, though a natural consequence of their complexity, leads to monolithic designs that are time-consuming a

researcharxiv-cs-ro

Derivative Computation in PINNs: Automatic Differentiation, Finite Differences and Beyond

model-releasesarxiv-cs-lg

arXiv:2608.11020v1 Announce Type: new Abstract: We systematically investigate finite-difference (FD) derivative computation in Physics-Informed Neural Networks (PINNs) as an alternative to automatic d

DistilVDR: A Compact End-to-End Visual Document Retriever via Dual-Student Distillation

model-releasesarxiv-cs-cl

arXiv:2608.10636v1 Announce Type: cross Abstract: Visual document retrieval (VDR) is dominated by multi-billion-parameter models that are slow to index at full corpus scale and expensive to serve. Pri

Distributional Uncertainty and Adaptive Decision-Making in System Co-design

arXiv:2603.14047v3 Announce Type: replace-cross Abstract: Complex engineered systems require coordinated design choices across heterogeneous components under conflicting objectives and uncertain speci

applicationsarxiv-cs-ro

Do LLMs Benefit From Their Own Words?

arXiv:2602.24287v2 Announce Type: replace-cross Abstract: In multi-turn conversations, large language models typically condition on the full conversation history: both past user prompts and assistant

Do Personalized Skills Help Coding Agents? An Empirical Study of Developer Interaction Histories

arXiv:2608.10319v1 Announce Type: cross Abstract: Large language model (LLM)-powered agents have rapidly evolved from code-completion tools into solvers of complex software engineering tasks. As devel

Does Explanation Correctness Matter? Linking Computational XAI Evaluation to Human Understanding

arXiv:2603.25251v2 Announce Type: replace-cross Abstract: Explainable AI (XAI) methods are commonly evaluated using functional correctness metrics, sometimes termed faithfulness or fidelity, which est

DreamOmni3: Scribble-based Editing and Generation

model-releasesarxiv-cs-cv

arXiv:2512.22525v2 Announce Type: replace Abstract: Recently unified generation and editing models have achieved remarkable success with their impressive performance. These models rely mainly on text

DualSpectralCF: Training-Free Sign-Aware Spectral Collaborative Filtering

arXiv:2608.10247v1 Announce Type: cross Abstract: Real-world recommendation platforms routinely collect explicit negative feedback such as 1-star reviews, hate-button clicks, distrust between users, a

ELVAE: Evidential Learning-Based Variational Autoencoder for Uncertainty-Aware Generation

arXiv:2608.10398v1 Announce Type: cross Abstract: Variational autoencoders generate samples from probabilistic latent representations but do not distinguish uncertainty about the latent location from

Enhancing Automated Essay Scoring With Three Techniques: Two-Stage Fine-Tuning, Score Alignment, and Self-Training

arXiv:2602.01747v2 Announce Type: replace Abstract: Automated Essay Scoring (AES) plays a crucial role in education by providing scalable and efficient assessment tools. However, in real-world setting

Evaluation-Conditioned Training: Teaching Models to Generalize to Stronger Oversight Regimes

arXiv:2608.10209v1 Announce Type: new Abstract: Feedback signals used to train Large Language Models (LLMs) are the primary driver of their behavior and our main lever for instilling alignment with hu

Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biases

arXiv:2608.10503v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed as autonomous agents, accurately evaluating their latent values and biases is critical. The NL

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

arXiv:2608.10954v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates signif

Exploration-Driven Personalized Federated Reinforcement Learning via Intrinsic Motivation

arXiv:2608.10499v1 Announce Type: cross Abstract: Personalized Federated Reinforcement Learning (PFRL) takes a decentralized approach to storing and accessing information based on past experiences whi

FaithformBench: Benchmarking Faithfulness of Mathematical Chain-of-Thought Autoformalisation

arXiv:2608.10916v1 Announce Type: cross Abstract: Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to asses

FedCGR: Federated Cross-Domain Generative Recommendation

arXiv:2608.10929v1 Announce Type: new Abstract: Cross-domain recommendation (CDR) transfers preference knowledge across related domains, but federated deployment makes cross-domain alignment difficult

FoR-SALE: Frame of Reference-guided Spatial Adjustment in LLM-based Diffusion Editing

arXiv:2509.23452v2 Announce Type: replace-cross Abstract: Current text-to-image generation models, even state-of-the-art models, exhibit a significant performance gap when spatial expressions are desc

From Prediction to Incrementality: Causal Optimization for Large-Scale Targeting and Recommendation

arXiv:2608.10182v1 Announce Type: cross Abstract: Large-scale targeting and recommendation systems are typically built around predictive scores fed into heuristic or local allocation. When the busines

HyperShape: Hyperelasticity Across Diverse Shapes

model-releasesarxiv-cs-lg

arXiv:2608.09938v1 Announce Type: cross Abstract: Hyperelastic deformations are highly sensitive to domain geometry and boundary conditions, making generalization across both a critical capability for

Inferential Capability Does Not Determine Legal Scope

arXiv:2608.10601v1 Announce Type: cross Abstract: Two instruments of EU digital law place inference at their centre and mean different things by it. Article 3(1) of the AI Act uses the capability to i

INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators

arXiv:2608.10492v1 Announce Type: new Abstract: Large Language Model (LLM)-based simulators often reproduce observable actions but fail to capture the underlying reasoning behind them. In education, w

Learning Disease-Sensitive Latent Interaction Graphs From Noisy Cardiac Flow Measurements

arXiv:2602.23035v2 Announce Type: replace Abstract: Cardiac blood flow patterns contain rich information about disease severity and clinical interventions, yet current imaging and computational method

LLM Agents Factory: Retrieval of Domain-Specific LLM Agents

arXiv:2608.09934v1 Announce Type: cross Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors. However, their practical deploymen

MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction

arXiv:2608.10562v1 Announce Type: new Abstract: Not all clicks are equal. Industrial ads ranking decouples conversion probability into click-through rate (CTR) and post-click conversion rate (CVR), ye

safetyarxiv-cs-lg

MD-ProTector: Positioning Multiple Data-Driven Prototypes for LLM-Generated Text Detection

arXiv:2608.10459v1 Announce Type: cross Abstract: As LLM-generated content becomes more sophisticated, detection systems for distinguishing those texts from human-written text must operate at scale wh

MT-PingEval: Evaluating Multi-Turn Collaboration with Private Information Games

arXiv:2602.24188v2 Announce Type: replace Abstract: We present a scalable and verifiable methodology for evaluating language models in multi-turn interactions, using a suite of collaborative games tha

agentsarxiv-cs-cl

Multiplayer Nash Preference Optimization

arXiv:2509.23102v4 Announce Type: replace Abstract: Reinforcement learning from human feedback (RLHF) has emerged as the standard paradigm for aligning large language models with human preferences. Ho

Navigation Alone Is Not Enough: Evaluating Explanatory Assistive UI Agents

arXiv:2608.09944v1 Announce Type: cross Abstract: Modern web interfaces are increasingly difficult to use with screen readers, particularly when pages update dynamically or hide important structure be

Nutrition Data Infrastructure for the AI Era: Operationalizing FAIR for Agent-Mediated Research

arXiv:2608.10363v1 Announce Type: new Abstract: AI agents can accelerate nutrition research, but their analyses inherit the identity, semantic, and release ambiguities of the underlying data. We prese

Local Ai

PBD-AG: Persistent Baseline-Delta Active Graphs with Uncertainty-Aware Inspection for Long-Horizon Service Robots

arXiv:2608.10449v1 Announce Type: new Abstract: Long-horizon service robots require persistent world models that can be built autonomously in unseen environments and revised as task-relevant objects c

local-aiarxiv-cs-ro

Position Encoding in Transformers: From Absolute and Relative Methods to Rotary Position Embeddings and Long-Context Scaling

arXiv:2608.10021v1 Announce Type: new Abstract: Self-attention models content-dependent interactions between tokens but does not by itself encode token order. Position encoding addresses this limitati