Search: “research”

All Roads Lead to Rome: Flow-driven Multi-Anchor Exploration for Open-Environment Active 3D Mapping

arXiv:2609.36889v1 Announce Type: new Abstract: To advance the development of embodied intelligence, Open-Environment Active 3D Mapping has attracted increasing attention, aiming to perform a long-hor

researcharxiv-cs-ro

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Research

Alpha Diffusion Language Models: Factorization Alone Is Not the Problem

DGX agent

arXiv:2609.38066v1 Announce Type: new Abstract: Discrete diffusion language models can generate multiple tokens in parallel, but reducing the number of denoising steps can lead to inconsistent predict

researcharxiv-cs-lg

30 Sept 2026

AMU:Admission and Memory Update for Personalized Conversations---Structured Memory with SLM Guided Control

arXiv:2609.36976v1 Announce Type: new Abstract: Large language models (LLMs) have become the foundation of personalized assistants, but maintaining persistent user memory across long-term interactions

researcharxiv-cs-cl

An Effective, Reliable, and Robust Framework for Human Activity Recognition Using Wearable Sensors

arXiv:2609.36848v1 Announce Type: new Abstract: Human Activity Recognition (HAR) through wearable sensors greatly improves the quality of human life through its multiple applications. For HAR, multi-s

An Efficient Machine Learning Approach for Degradation Forecasting in AEM Water Electrolysis

arXiv:2609.37941v1 Announce Type: new Abstract: This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constan

Aperture: Merge-Consistent Rotary States for Compressed Tokens

arXiv:2609.36781v1 Announce Type: new Abstract: Token compression combines content from several positions, yet rotary position embeddings usually assign the merged token one coordinate. We ask what po

Safety

Applying Language Models in Clinical Medicine: Recent Trends and Perspectives

arXiv:2609.34780v2 Announce Type: replace Abstract: The use and applicability of artificial intelligence (AI) in medical research and clinical practice has received increasing attention in the literat

safetyarxiv-cs-ai

Are In-Context Images Worth 10 Dimensions?

arXiv:2609.37659v1 Announce Type: new Abstract: There has been significant work on understanding the In-Context Learning capabilities of Large Language Models, especially on the induction circuit. For

ARGOS: Reinforcement Learning-Driven Multidimensional Elasticity for Service Orchestration in the Computing Continuum

arXiv:2609.37085v1 Announce Type: cross Abstract: Data-intensive services in the Computing Continuum must balance analytics quality, resource usage, and cost across heterogeneous nodes with limited an

AS^2D: Accelerating On-Demand Audio Understanding on Mobile Devices

arXiv:2609.37617v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive generation by using a smaller drafter to propose tokens for batched verification by a larger target. H

Model Releases

ASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations

model-releasesarxiv-cs-ai

arXiv:2609.32868v2 Announce Type: replace-cross Abstract: Traditional scientific computing requires researchers to translate computational intent into environment configuration, resource requests, and

ATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning

arXiv:2609.36333v1 Announce Type: cross Abstract: Latent world models rely on representation geometry for planning, yet regularizing the latent marginal alone does not determine the state-to-state rel

Attention-Scoped Guidance: Training-Free Spatial Control for Image Editing

arXiv:2609.37492v1 Announce Type: new Abstract: Instruction-guided image editing should change what the instruction names and leave the rest of the image untouched. In dual classifier-free guidance (C

Authority Before Utility: Non-Compensatory Control for Persistent LLM Memory

arXiv:2609.37474v1 Announce Type: new Abstract: Persistent memory creates a control problem that retrieval relevance alone does not solve: a memory can remain highly useful after an update, deletion,

Backdoor Mitigation in Decentralized LLM Fine-Tuning

arXiv:2609.37367v1 Announce Type: cross Abstract: Decentralized large language model (LLM) fine-tuning lets organizations collaboratively train a shared LLM on data they cannot pool, without a central

BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

arXiv:2406.00083v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by retrieving relevant information from external knowledge bases to

BarcodeMAE+: Rethinking Masked Pretraining and Global Representations for DNA Barcode Foundation Models

arXiv:2609.35877v1 Announce Type: cross Abstract: Many DNA foundation models are pretrained by masking parts of a sequence and asking the model to reconstruct them. Standard masked pretraining exposes

Behavioral Capacity Certificates for Quantized Language Models

arXiv:2609.37887v1 Announce Type: new Abstract: Activation and key-value cache precision change what a quantized language model computes without altering its stored weights. Direct weight-code bounds,

Behavioral Convergence Without Representational Convergence: Persistent Training-History Dependence in Neural Networks

arXiv:2609.37836v1 Announce Type: new Abstract: Neural networks trained toward the same final objective can reach similar predictive performance while retaining internal representations shaped by earl

Benchmarking Vision-Language Models on Synapse Detection and Proofreading in Connectomics

arXiv:2609.36492v1 Announce Type: cross Abstract: We benchmarked vision-language models (VLMs) on the decisions annotators take when inspecting electron microscopy images in connectomics: synapse dete

Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning

arXiv:2609.36359v1 Announce Type: new Abstract: Graph-based approximate nearest neighbor search (ANNS) is widely used for large-scale semantic search. Its indices are constructed primarily based on ge

Beyond Attention Imbalance: Mitigating Hallucinations via Spectral Surgery

arXiv:2609.37263v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs) achieve remarkable success, hallucinations remain a significant barrier to their reliable deployment. Recent

Beyond Readability: Evaluating Task Information Recoverability

arXiv:2609.36957v1 Announce Type: new Abstract: Direct visual readability and task-information recoverability are different quantities. Failure to decode a target from a fixed observation need not eli

Beyond Semantic Narrowing: Robust and Efficient LLM Watermarking with Hamming Neighborhoods

arXiv:2609.37218v1 Announce Type: cross Abstract: Semantic watermarking improves robustness against watermark removal attacks by embedding detectable signals into sentence-level representations. Howev

Beyond the Timeline: Augmenting Long-Video Memory with Grounded Entity Biographies

arXiv:2609.38155v1 Announce Type: cross Abstract: Answering questions about long videos often requires connecting events involving the same objects across hours or days. Chronological descriptions and

Beyond Token Importance: Preserving Spatial Scaffolds for Efficient Vision-Language-Action Inference

arXiv:2609.36967v1 Announce Type: new Abstract: Existing VLA pruning strategies primarily select individual visual tokens according to task-level semantic relevance, while overlooking the spatial info

researcharxiv-cs-ro

Bits Under ZK-LLM: Evaluating Zero-Knowledge-Friendly Quantization for Verifiable Private LLM Inference

arXiv:2609.36437v1 Announce Type: new Abstract: Zero-knowledge proofs are emerging as a promising approach for enabling private, verifiable LLM governance and auditing, where regulators, users, and au

Boosting Metric Depth Completion via Training-Free Adaptive Response Geometry

arXiv:2609.36168v1 Announce Type: new Abstract: Depth completion aims to recover dense metric depth from sparse sensor measurements, increasingly leveraging visual foundation models as geometric prior

Breakdown of Local Denoising as Semantic Speciation

arXiv:2609.38176v1 Announce Type: new Abstract: The dynamics of generative models exhibit two apparently distinct temporal windows: a speciation window, in which a sample commits to a semantic class,

Breaking the Illusion of Review Reliability under Static Evaluation: SCOPE Fuzzing for LLM-based Scientific Reviewers

arXiv:2609.37097v1 Announce Type: new Abstract: The rapid growth of submissions and reviewing workload has accelerated the use of large language models (LLMs) in peer review. Prior studies suggest tha

ByteTraX: Enhancing the ByteTrack Architecture with Optimised Thresholding

arXiv:2609.37801v1 Announce Type: new Abstract: The ByteTrack algorithm is a widely used and computationally efficient multi-object tracking architecture. Its core innovation lies in the combination o

CAD-Native Transformer Operators for AI-Aided Engineering

arXiv:2609.36806v1 Announce Type: new Abstract: Modern engineering systems, from automobiles to aircraft, are designed by using precise, continuous parametric computer-aided design (CAD) models. Evalu

CADENCE: A Confidence-Adaptive Dual-Expert Network for Fast and Accurate Time Series Classification

arXiv:2609.35929v1 Announce Type: new Abstract: Time series classification (TSC) exhibits a sharp trade-off between accuracy and computational scalability. Meta-ensembles like HIVE-COTE 2.0 reach stat

Calibrated to Whom? Persona and Language Effects on Cultural Values in JEV

arXiv:2609.36399v1 Announce Type: cross Abstract: Decision-only language models return a probability for every answer option instead of generating text, which makes them attractive as survey responden

Calibrating One-Round Membership Inference with Neighbors

arXiv:2609.36331v1 Announce Type: cross Abstract: The state-of-the-art Membership Inference (MI) methods calibrate their signal separately for each example using reference models, auxiliary models tra

Can a Cacheable Decision Model Follow Rules?

arXiv:2609.37832v1 Announce Type: new Abstract: Certo is a small non-generative decision model (Qwen3-4B): it scores candidate actions from their text and returns a probability, instead of generating

Can We Still Trust Disaster Social Sensing? Empirical Evidence on Detecting AI-Generated Social Media Posts

arXiv:2609.35821v1 Announce Type: new Abstract: Disaster social sensing converts public social-media posts into evidence for situational awareness and humanitarian needs, but generative artificial int

researcharxiv-cs-cl

Challenges and Solutions for Bandits in the Wild: Warm-Started Mixture Bandits for Cross-Cohort Slate Recommendation

arXiv:2609.37800v1 Announce Type: cross Abstract: Many recommender services repeatedly encounter cold-start cohorts, where new users arrive with little or no interaction history. This creates two chal

Cheap and Powerful Tests for Supervised Subspaces: Per-Component Inference for PLS

arXiv:2609.36307v1 Announce Type: new Abstract: Partial Least Squares (PLS) regression extracts a few outcome-aligned directions in a high-dimensional X and is widely used across applied science, but

Model Releases

Cloud CISO Perspectives: How cybersecurity startups can win CISOs

model-releasesgoogle-cloud-ai

Welcome to the second Cloud CISO Perspectives for September 2026. Today, Alicja Cade and Nick Godfrey, senior directors, Office of the CISO, share their guidance for cybersecurity startups on how to w

Communication-Efficient Agnostic Federated Learning via Faster Convergence and Compression

arXiv:2609.36610v1 Announce Type: new Abstract: Agnostic federated learning (AFL) seeks a model that performs reliably across m heterogeneous workers, but communication remains a bottleneck. We improv

Comparing Utility of Inertial, Occupancy, Semantic, and Intent Information in Human Motion Prediction During Daily Tasks

arXiv:2609.37971v1 Announce Type: new Abstract: Accurate human motion prediction is crucial for robotic systems operating around people, particularly in complex indoor spaces. In this study, we assess

researcharxiv-cs-ro

Concept Direction Reliability Across Languages with Different Tokenizer Fertility

arXiv:2609.36194v1 Announce Type: new Abstract: Extracted sentiment directions can vary across samples even when downstream sentiment classification remains accurate. To evaluate direction reproducibi

researcharxiv-cs-cl

Context without Commitment: Robust Dense Correspondence under Non-Rigid Deformation

arXiv:2609.37071v1 Announce Type: new Abstract: Non-rigid point-cloud registration aims to find the corresponding target point for each point on a deforming source surface. Point-level matching keeps

Convex Physics Informed Neural Networks for the Monge-Ampere Optimal Transport Problem

arXiv:2501.10162v3 Announce Type: replace-cross Abstract: Optimal transportation of raw material from suppliers to customers is an issue arising in logistics that is addressed here with a continuous m

Correct, Don't Delete: Mitigating Emergent Misalignment with Corrective Supervision

arXiv:2609.37624v1 Announce Type: cross Abstract: Fine-tuning a language model on a narrow set of harmful demonstrations, such as bad medical advice, can make it broadly misaligned on unrelated questi

CPATTA: Conformal Supervision Allocation For Active Test-Time Adaptation

arXiv:2509.25692v2 Announce Type: replace-cross Abstract: Active Test-Time Adaptation (ATTA) improves model robustness under domain shift by selectively querying human annotations at deployment, but e

Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data

arXiv:2609.38165v1 Announce Type: new Abstract: The landscape of satellite imagery time series datasets and boundary-pushing architectures for cropland segmentation has never been richer. However, in