All entries

Constraint-Aware Discrete Black-Box Optimization Using Tensor Decomposition

arXiv:2609.09370v1 Announce Type: new Abstract: Discrete black-box optimization is often addressed using approaches such as Sequential Model-Based Optimization (SMBO), which aims to improve sample eff

applicationsarxiv-cs-lg

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Contrastive Projection: Reading Transformer Internals by Differencing Logit Lenses

DGX agent

arXiv:2609.09902v1 Announce Type: new Abstract: Reading a transformer's internal states in token space is easy to do and hard to trust: a logit lens on a single hidden state is dominated, at intermedi

model-releasesarxiv-cs-cl

10 Sept 2026

Control Copy-Paste: Controllable Diffusion-Based Augmentation Method for Remote Sensing Few-Shot Object Detection

arXiv:2507.21816v1 Announce Type: cross Abstract: Few-shot object detection (FSOD) for optical remote sensing images aims to detect rare objects with only a few annotated bounding boxes. The limited t

safetyarxiv-cs-cv

ConvMem: Convolutional Memory for Long-Context Reasoning

arXiv:2609.10441v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated impressive capabilities, they often struggle with extremely long contexts due to fixed context li

researcharxiv-cs-cl

Copying explains the collective behavior of AI agents in the wild

model-releasesarxiv-cs-cl

arXiv:2609.09150v2 Announce Type: replace-cross Abstract: In June 2026, thousands of AI agents found that a small public wiki would accept edits from inside their sandboxes, and started using it to he

Cost-Aware Post-Hoc Deferral Under Calibration and Shift: An Environmental AI Case Study

arXiv:2609.09235v1 Announce Type: cross Abstract: Choosing a deferral policy for a frozen classifier requires more than ranking uncertain cases: confidence may be miscalibrated, errors have unequal co

safetyarxiv-cs-lg

CougarTail & CUB: A General-Purpose Mast and Central Utility Board for Cylindrical Underwater Enclosures

arXiv:2609.10230v1 Announce Type: new Abstract: Cylindrical watertight enclosures are widely used across various underwater systems, from unmanned underwater vehicles (UUVs), to remotely operated vehi

researcharxiv-cs-ro

Critical initialization destabilizes higher input derivatives in wide scalar-input networks

arXiv:2609.09244v1 Announce Type: cross Abstract: The edge-of-chaos condition preserves first-order input perturbations in wide randomly initialized networks, but physics-informed losses, score matchi

CriticGen: Generation-Aware Evaluation as Actionable Feedback

arXiv:2609.05439v1 Announce Type: new Abstract: Current evaluation methods for large language models are coarse-grained and decoupled from generation, producing generic explanations that fail to provi

researcharxiv-cs-ai

Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.10495v1 Announce Type: new Abstract: In real-time colonoscopy, ground-truth annotations are unavailable at inference, so polyp segmentation models can fail silently. We propose Referee-Base

Tutorials

Cross-Species Animal Re-Identification with Semantic Consistency Learning

arXiv:2609.09705v1 Announce Type: new Abstract: Generalizable animal Re-Identification (ReID) aims to recognize individual animals across species with diverse morphologies and ecological contexts. Unl

tutorialsarxiv-cs-cv

CT-SAFR: Safe and Interpretable Chain-of-Thought Reasoning for Autonomous Robots: A Multi-Layered Verification Framework for Trustworthy AI-Driven Robotic Decision Making

arXiv:2609.09692v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting enables LLMs to perform explicit, step-by-step reasoning, creating opportunities for sophisticated autonomous robots. H

safetyarxiv-cs-ro

CTC-TTS: LLM-based dual-streaming text-to-speech with CTC alignment

arXiv:2602.19574v2 Announce Type: replace-cross Abstract: Large-language-model (LLM)-based text-to-speech (TTS) systems can generate natural speech, but most are not designed for low-latency dual-stre

safetyarxiv-cs-ai

Customer Relationship Intelligence: Integrating CRM and MDM for Enhanced Customer Engagement

arXiv:2609.06189v1 Announce Type: new Abstract: This study examines how Customer Relationship Management (CRM), Master Data Management (MDM), and Customer Knowledge Management (CKM) jointly constitute

applicationsarxiv-cs-ai

CWF: A Collaborative Writing Framework for Personalized and Reliable Popular Science Writing

arXiv:2609.06126v1 Announce Type: new Abstract: We introduce Personalized and Reliable Popular Science Writing, a novel task that requires adapting scientific explanations to audiences with different

Cyber-Financial Contagion: Modeling the Propagation of an AI Vendor Compromise Through the Banking System

arXiv:2609.10350v1 Announce Type: cross Abstract: The banking system now depends on a small set of shared artificial intelligence vendors for fraud screening, credit decisioning, anti-money-laundering

Local Ai

D-ADD: An Effective Plug-In for Defending Against Model Stealing

arXiv:2503.12497v2 Announce Type: replace-cross Abstract: Malicious users attempt to replicate commercial models functionally at low cost by training a clone model with query responses. Timely prevent

local-aiarxiv-cs-ai

DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents

arXiv:2609.06059v1 Announce Type: new Abstract: As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to as

DART: A DAG-Based Reputation and Incentive Framework via Blockchain-Enabled Governance for Trustworthy LLM Multi-Agent Collaboration

arXiv:2609.05529v1 Announce Type: cross Abstract: Large language model (LLM)-based multi-agent systems (MAS) predominantly rely on centralized orchestration and lack formal verification mechanisms for

safetyarxiv-cs-ai

Data-Centric Post-Training for Financial Reasoning: Mining, Distillation, and Verifiable Learning

arXiv:2609.10113v1 Announce Type: new Abstract: Financial text, textbooks, and question-answer pairs are abundant, but only a small fraction is directly usable for reasoning-focused post-training. Exi

applicationsarxiv-cs-cl

Data-Driven Risk Fields for Safer End-to-End Autonomous Driving

arXiv:2609.10377v1 Announce Type: cross Abstract: Safety is a fundamental requirement for autonomous driving, yet existing end-to-end driving models still lack explicit risk-aware learning capacities.

safetyarxiv-cs-cv

DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration

model-releasesarxiv-cs-cv

arXiv:2509.06285v2 Announce Type: cross Abstract: LiDAR point cloud registration is fundamental to robotic perception and navigation. In geometrically degenerate environments (e.g., corridors), regist

Dead Directions: Geometric Singular Learning

arXiv:2606.05957v2 Announce Type: replace Abstract: Singular learning theory and information geometry study the same spaces: the former in resolved coordinates, the latter in original coordinates unde

Decision-Focused Active Learning for Scale-Aware Critical-Materials Recovery

model-releasesarxiv-cs-ro

arXiv:2609.09413v1 Announce Type: cross Abstract: Choosing a recovery process for scale-up requires connecting laboratory results with product requirements, process costs, and scale effects. We analyz

Decision Transformer for UAV-Mounted RIS-Assisted Dynamic D2D Communications

arXiv:2609.09885v1 Announce Type: cross Abstract: This paper studies unmanned aerial vehicle (UAV)-mouted reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication with st

researcharxiv-cs-ro

Decoupled Self-Forcing Distillation for Streaming Talking Head Generation

arXiv:2609.10317v1 Announce Type: new Abstract: Streaming talking-head generation produces each frame as its driving audio arrives, yet fidelity and efficiency have so far pulled in opposite direction

safetyarxiv-cs-cv

Deep and shallow biases in language models

arXiv:2609.09901v1 Announce Type: new Abstract: Large language models often repeatedly select the same answer even when many alternatives are plausible. Prior work treats this concentration as bias, b

safetyarxiv-cs-cl

Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems

model-releasesarxiv-cs-lg

arXiv:2609.10479v1 Announce Type: cross Abstract: More Electric Aircraft require fast and reliable monitoring of high-frequency electrical networks, yet most power quality disturbance and fault diagno

Deep Neural Networks for Learning Intent from sEMG Signals to Support Hardware Devices for Post-Stroke Neurorehabilitation

model-releasesarxiv-cs-lg

arXiv:2609.09971v1 Announce Type: new Abstract: Finger-specific motor intent is a clinically meaningful control signal for post-stroke neurorehabilitation, where residual muscle activity may remain me

Deformable Object Manipulation under Partial Observability via Real-Time Full-Shape Estimation

model-releasesarxiv-cs-ro

arXiv:2609.10308v1 Announce Type: new Abstract: Manipulating deformable objects (DOs) is challenging due to their high-dimensional state space, underactuated dynamics, and partial observability. In th

DensePol: Dense-Angle Polarization Dataset for Learning-Based Polarimetric Vision

arXiv:2609.09359v1 Announce Type: new Abstract: Polarimetric vision is gaining increasing attention because it provides physical cues about scene shape, material, and reflection that are difficult to

researcharxiv-cs-cv

Design and Attitude Control of an Underwater Quadruped Robot

arXiv:2609.09217v1 Announce Type: new Abstract: Legged robots are versatile on land, but their use in underwater environments remains limited. Extending quadruped locomotion to water enables amphibiou

researcharxiv-cs-ro

Deterministic Prompting for Speaker-Stable Low-Resource Greek TTS

arXiv:2609.10022v1 Announce Type: cross Abstract: Modern TTS systems approach human quality for high-resource languages but degrade when clean speech data is scarce. Modern Greek exemplifies this, lac

safetyarxiv-cs-cl

Local Ai

Detokenization Leaks: Reconstructing Local LLM Outputs From Cache Traces

arXiv:2609.06674v1 Announce Type: cross Abstract: We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prio

local-aiarxiv-cs-ai

Development and Validation of a Physics-Guided Machine Learning Extrapolation Framework Using a Classical Transient Diffusion Benchmark

model-releasesarxiv-cs-lg

arXiv:2609.09912v1 Announce Type: new Abstract: Machine learning models used in engineering are typically trained within limited operating ranges, yet reliable predictions are often required beyond th

DFNN: A Deep Frechet Neural Network Framework for Learning Metric-Space-Valued Responses

arXiv:2510.17072v2 Announce Type: replace-cross Abstract: Regression with non-Euclidean responses---e.g., probability distributions, networks, symmetric positive-definite matrices, and compositions---

applicationsarxiv-cs-lg

DGCPath: Distribution-Aware Generative Contrastive Framework for Self-supervised Path Representation Learning -- Extended Version

arXiv:2609.07316v2 Announce Type: new Abstract: Due to the proliferation of vehicle trajectory data enabled by advanced sensing technologies, path representation learning has become a pivotal task in

safetyarxiv-cs-ai

DI-Bench: Systematically Generating In-Domain Data Intelligence Benchmarks for Enterprise Agents

arXiv:2609.05776v1 Announce Type: new Abstract: Evaluating enterprise agents on domain-specific benchmarks is critical, yet public benchmarks rarely evaluate whether agents can integrate business know

Agents

Diamond Agent: Agentic Control of Federated HPC Resources as a Service

arXiv:2609.06181v1 Announce Type: cross Abstract: Efficiently aggregating and orchestrating computing power across heterogeneous clusters for HPC workflows faces four practical challenges: preserving

agentsarxiv-cs-ai

Differentially Private Average Treatment Effect Estimation by Propensity Score Blocking

arXiv:2609.09536v1 Announce Type: cross Abstract: Average treatment effect (ATE) estimation in observational studies is a fundamental statistical tool used frequently in social science, medicine, and

safetyarxiv-cs-lg

Tutorials

DiffLUT-Net: Differentiable Training of FPGA LUT Networks with Learnable Connectivity

arXiv:2609.09254v1 Announce Type: new Abstract: Field-programmable gate arrays (FPGAs) enable efficient neural-network inference, but most deployment flows either accelerate multiply-accumulate operat

tutorialsarxiv-cs-lg

Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

arXiv:2609.05779v1 Announce Type: cross Abstract: Large language models used for code editing can be trained and deployed in at least two output regimes: direct generation, where the model emits the e

Dimensionality Reduction for Hyperspectral Image Classification

arXiv:2609.10334v1 Announce Type: new Abstract: This paper addresses the issue of supervised classification in the context of hyperspectral satellite images. It deals with two fundamental aspects: dim

researcharxiv-cs-cv

Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training

arXiv:2609.10052v1 Announce Type: new Abstract: LLM agents for sequential decision tasks are often post-trained with trajectory-level outcome labels, but such labels provide little supervision for pre

researcharxiv-cs-cl

Local Ai

DiSCo: A Distribution-First Steering and Cultural Prior Evaluation Framework for Measuring Cultural Preference Bias in LLMs

arXiv:2609.10253v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in globally used assistants, yet their default choices in culturally grounded everyday situations

local-aiarxiv-cs-cl

Distance-Aware Attention and Wall-Distance Expert Routing for Transformer-Based 3D Flow Prediction

arXiv:2609.07222v1 Announce Type: new Abstract: Transformer surrogates for 3D flow prediction compress an industrial mesh into a small set of tokens from which every prediction point reads. Two operat

researcharxiv-cs-ai

Distillation of Synthetic Data for Time Series Foundation Models

arXiv:2609.09586v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are increasingly pre-trained on synthetically generated time series trajectories, where the data generating proc

Distilling Image Prototypes for Guided Test-Time Adaptation

arXiv:2609.09737v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) enhances the robustness of models against distribution shifts but faces two critical challenges: error accumulation from nois

researcharxiv-cs-cv