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Configurable Semantic Chunking for Biomedical Information Extraction in Retrieval-Augmented Generation

arXiv:2608.31139v1 Announce Type: new Abstract: BioMedRAG introduced retrieval-augmented generation with a learned chunk scorer for biomedical information extraction. However, it relies on fixed-size

researcharxiv-cs-cl

Content type

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Safety

Confounding Masquerading as Improvement: A Systematic Evaluation of Offline Reinforcement Learning for Stroke Antithrombotic Treatment in a 129,000-Patient Registry

DGX agent

arXiv:2608.30442v1 Announce Type: new Abstract: Recent offline reinforcement learning (RL) studies report policies that outperform physician decisions on clinical outcomes. We conduct a systematic, pa

safetyarxiv-cs-lg

1 Sept 2026

Conjoint Audio-to-Spikes Encoding and Processing for Efficient Neuromorphic Speech Recognition

model-releasesarxiv-cs-ai

arXiv:2608.30792v1 Announce Type: cross Abstract: Obtaining data from neuromorphic sensors and processing it with Spiking Neural Networks is a promising solution to lower the energy cost of artificial

Conservative Hybrid Graph Networks for Process Systems with Learned Routing

arXiv:2608.28896v1 Announce Type: new Abstract: Industrial process networks do not maintain a single effective topology while operating: streams are throttled or bypassed, and units move between idle,

Constant Individual Regret in General Games

arXiv:2608.31166v1 Announce Type: new Abstract: Uncoupled no-regret dynamics provide a decentralized route to equilibrium, but prior guarantees for individual regret retain a polylogarithmic dependenc

Constrained Group Relative Policy Optimization

arXiv:2602.05863v3 Announce Type: replace-cross Abstract: Group Relative Policy Optimization (GRPO) remains the dominant critic-free approach for fine-tuning LLMs and VLMs, but its compatibility with

Content Exploration Beyond the Feed: Creator Supply and the Shared Corpus

arXiv:2608.29430v1 Announce Type: cross Abstract: Industrial recommenders give new content initial views through budgeted exploration, then use early performance to decide further delivery. On many sh

applicationsarxiv-cs-lg

Context-Aware Interleaved Batching for WhisperX

arXiv:2608.31170v1 Announce Type: new Abstract: While WhisperX accelerates speech transcription via intra-audio batching, it isolates audio segments, losing the historical context needed for coherent

researcharxiv-cs-cl

Context-Aware Interpretable Representations for Retrieval and Graph Convolutional Network Classification

arXiv:2608.29004v1 Announce Type: cross Abstract: The advances in visual information modeling and representation during the last decades are remarkable, mainly supported by Convolutional Neural Networ

safetyarxiv-cs-cv

Context Staircase: Signature-Aligned Dynamics of Token Embeddings under Small Initialization

arXiv:2608.30315v1 Announce Type: cross Abstract: Token embeddings are the basic representational units that connect discrete tokens with continuous computation in language models. Although modern lan

safetyarxiv-cs-cl

ContextBias: Controlled Evaluation of Bias Persistence Under Context Shift in Text-to-Image Models

arXiv:2608.29847v1 Announce Type: cross Abstract: Text-to-image models learn associations between concepts - in the case of this paper, people's professions, which we refer to as roles - and visual at

Continual Test-Time Adaptation via Entropy Sensitivity-Guidance in Strict Online Setting

arXiv:2608.29920v1 Announce Type: new Abstract: Test-time adaptation (TTA) promises robustness under distribution shift by updating a pretrained model on unlabeled test data, but strict online TTA wit

Continuity-Free Near-Minimax Leading-Order Regret for CVaR-UCBVI

arXiv:2608.28960v1 Announce Type: new Abstract: For finite-horizon tabular CVaR reinforcement learning, prior work proves a widetilde{O}(au^{-1}sqrt{SAK}) leading regret bound for arbitrary normalized

Contrast-Free Autonomous Navigation of Untethered Endovascular Microrobots Using Single-Plane Fluoroscopy

arXiv:2608.30220v1 Announce Type: new Abstract: Reliable three-dimensional (3D) navigation of magnetically actuated untethered microrobots remains a major barrier to clinical translation. X-ray fluoro

agentsarxiv-cs-ro

Controllable Memory Usage: Balancing Anchoring and Innovation in Long-Term Human-Agent Interaction

arXiv:2601.05107v2 Announce Type: replace Abstract: As LLM-based agents are increasingly used in long-term interactions, cumulative memory is critical for enabling personalization and maintaining styl

agentsarxiv-cs-ai

Controlling Refusal Behavior of LLMs via Stiefel-Constrained Rotation Steering

arXiv:2608.30986v1 Announce Type: cross Abstract: Activation steering has emerged as a lightweight approach for controlling model refusal at inference time. A growing line of research explores trainab

Convergence rates for the RMSprop optimizer with full control of the hyperparameters

model-releasesarxiv-cs-lg

arXiv:2608.30382v1 Announce Type: new Abstract: Popular adaptive stochastic gradient descent (SGD) methods to train artificial intelligence (AI) systems include the RMSprop, the Adam, and the AdamW op

Converse and Collision-Based Achievability for Node Localization with Hybrid Distance-Spectral Graph Positional Encodings

arXiv:2608.30152v1 Announce Type: new Abstract: Graph positional encodings are widely used in graph neural networks and graph Transformers, yet it remains unclear when the code itself can identify nod

CORAL: A Benchmark for Structure-aware and Brain-wide Neuron Reconstruction in Light Microscopy

model-releasesarxiv-cs-cv

arXiv:2608.30768v1 Announce Type: new Abstract: Automatic neuron reconstruction from light microscopy images is a central problem in computational neuroanatomy. While recent methods have achieved enco

CoRe-GS: Coarse-to-Refined Gaussian Splatting with Semantic Object Focus

arXiv:2509.04859v4 Announce Type: replace Abstract: Fast and efficient photorealistic 3D reconstruction with (semantic) Gaussian Splatting (GS) is crucial for time-critical robotic perception and navi

applicationsarxiv-cs-cv

Tutorials

CoReflect: A Reflective Co-Evolution Framework for Improving Conversational Evaluation

arXiv:2601.12208v2 Announce Type: replace Abstract: Evaluating conversational systems in multi-turn settings remains a fundamental challenge. Conventional pipelines typically rely on manually defined

tutorialsarxiv-cs-cl

Coronary Mask Guided Registration for Continuous Time 4D Cardiac CT Dataset Construction

arXiv:2608.28712v1 Announce Type: cross Abstract: Objective: Clinical cardiac CT multiphase reconstructions generally provide acceptable image quality in end-diastole (ED) or end-systole (ES) phases,

Correctness Forensics for Batch Speculative Decoding: Diagnosing the Ragged Tensor Problem

arXiv:2510.22876v4 Announce Type: replace-cross Abstract: Inference optimizations are routinely evaluated by throughput alone, without verifying output correctness. We conduct a forensic analysis of b

safetyarxiv-cs-ai

Local Ai

Cost-Effective Repository Exploration for Agentic Issue Localization

arXiv:2608.29675v1 Announce Type: cross Abstract: Repository exploration is a distinct and costly stage of coding-agent pipelines: before generating a patch, an agent must identify which repository fi

local-aiarxiv-cs-ai

Cost-efficient Active Learning for Referring Image Segmentation and Grounding

arXiv:2608.30621v1 Announce Type: cross Abstract: Collecting natural-language referring expressions along with region annotations, such as masks or boxes, is a major bottleneck in visual grounding (VG

CoVA-SFT: A Large-Scale Dataset for Chain of Visual Abstractions

arXiv:2608.28958v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has dramatically improved large language models (LLMs) by allowing them to decompose problems into intermediate steps.

CPR for LLMs: Critical-Point Routing against Catastrophic Forgetting in Domain Adaptation

arXiv:2608.30158v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) is the de facto standard for adapting large language models (LLMs) to target domains, but it often degrades the model's g

Local Ai

Creation begins with understanding: LLMs as strategy designers for privacy-preserving tabular data synthesis

arXiv:2608.29674v1 Announce Type: new Abstract: Sharing tabular data in high-stakes domains is constrained by privacy regulations. Synthetic data offer a promising alternative, but deep generative mod

local-aiarxiv-cs-lg

Cross-lingual Functional Vectors for Emotion Detection in Large Language Models

arXiv:2608.29613v1 Announce Type: new Abstract: Function vectors (FVs) have recently emerged as a promising mechanism for steering the behavior of large language models (LLMs) by injecting task-specif

Cross Lingual Transfer in Tulu Legal Comprehension: Script-Dependent Improvement and RAG-Induced Knowledge Conflict

arXiv:2608.28645v1 Announce Type: cross Abstract: Low-resource languages without an adequate training corpus often use a related, higher-resource language as a scaffold for comprehension. Still, there

applicationsarxiv-cs-ai

Cross-Modal Visuo-Tactile Representation Learning with Action Chunking Transformers for Contact-Rich Manipulation

arXiv:2602.00514v3 Announce Type: replace Abstract: Tactile feedback is important for contact-rich robotic manipulation, yet effective use of tactile observations remains challenging when tactile sign

safetyarxiv-cs-ro

Cross-Regional Grapevine Cold Hardiness Prediction via Learned Multimodal Latent Representations

arXiv:2608.31097v1 Announce Type: new Abstract: Accurate daily predictions of cold hardiness in woody plants are critical in regions where freezing temperatures can damage dormant buds and reduce seas

Cross-Relational Preference Learning for Better LLM Instruction Following

arXiv:2608.29352v1 Announce Type: new Abstract: Large Language Models (LLMs) still exhibit limited capability in following complex instructions. While existing approaches often rely on preference lear

CrossAudit: A Git-Native, Cross-Vendor Audit Loop for Agentic Science

arXiv:2608.28631v1 Announce Type: new Abstract: An AI scientist should not grade its own homework. Yet in the systems we examined, the agent that reviews the work usually comes from the same model fam

agentsarxiv-cs-ai

Hardware

CrowdStrike builds security frontier models with Nvidia and opens an AI lab

CrowdStrike Holdings Inc. today launched SafeMind, a family of artificial intelligence models and agent harnesses created with Nvidia Corp. and built for security work rather than general use. A resea

hardwaresiliconangle

CrowdStrike launches Falcon Guardian to police AI agents at the endpoint

model-releasessiliconangle

CrowdStrike Holdings Inc. today unveiled Falcon Guardian, software that finds the artificial intelligence agents running inside a company and shuts down the ones security teams have not approved. The

Curvature Cryptanalysis of Smooth Transformer Feed-Forward Networks

model-releasesarxiv-cs-ai

arXiv:2608.28843v1 Announce Type: cross Abstract: We show that smooth two-layer feed-forward networks (FFNs) expose an additional structural model extraction channel under a chosen-input raw-output or

Hardware

D4orm: Multi-Robot Trajectories with Dynamics-aware Diffusion Denoised Deformations

arXiv:2503.12204v3 Announce Type: replace Abstract: This work presents an optimization method for generating kinodynamically feasible and collision-free multi-robot trajectories that exploits an incre

hardwarearxiv-cs-ro

Hardware

Dancing Stick Figures: An Introductory Dataset for Training Video Generation Models

arXiv:2608.29123v1 Announce Type: new Abstract: Training a video-generation model from scratch is hard for reasons that precede model design. The feedback loop is long: a failure that appears only aft

hardwarearxiv-cs-cv

DARD: Zero-Shot Degradation-Aware Retinex-Guided Diffusion for Low-Light Image Enhancement

arXiv:2608.29243v1 Announce Type: new Abstract: Existing diffusion-based enhancement methods provide strong generative capability for low-light image enhancement (LLIE), yet they either rely on paired

applicationsarxiv-cs-cv

DARP: A Calibrated Dual-Arm RGB-D-IR Dataset for Multi-View Robotic Perception

arXiv:2608.31002v1 Announce Type: cross Abstract: Robotic perception from a single viewpoint is often limited by self-occlusion and incomplete surface visibility. This paper presents DARP(Dual-Arm Rob

DART: Draft-Agreement Routing for Training-Free Adaptive Thinking Budgets in Hybrid Reasoning Models

arXiv:2606.23181v2 Announce Type: replace Abstract: Hybrid reasoning models can answer directly or spend extra tokens on extended thinking. A practical router should choose between these modes for eac

DASC: Decay-Aware State Compression for Hybrid Linear-Attention Serving

model-releasesarxiv-cs-ai

arXiv:2608.30386v1 Announce Type: cross Abstract: Hybrid linear-attention architectures have recently scaled to large open-weight models, offering quality competitive with full attention while substan

Data-Centric Neuromotor Interfaces for Portable Human-Machine Interaction

model-releasesarxiv-cs-ro

arXiv:2608.30301v1 Announce Type: new Abstract: Dexterous human-machine interaction requires intuitive and expressive interfaces that can be efficiently deployed on constrained edge devices. Flexible

Data Diversity, Not Frequency Invariance: A Controlled and Self-Audited Study of Compression-Robust Deepfake Detection

arXiv:2608.28685v1 Announce Type: new Abstract: Frequency features and compression-invariant representation learning are widely assumed to be key to deepfake detection that survives video compression.

Data-Driven Design Optimization of Streaming-Potential-Mediated Electrokinetic Transport of Viscoelastic Fluids in Microchannels

model-releasesarxiv-cs-lg

arXiv:2608.29939v1 Announce Type: cross Abstract: Streaming-potential-mediated transport of viscoelastic fluids has attracted research attention owing to its applications in electrokinetic energy conv

Data Intelligence Agents: Interpreting, Modeling, and Querying Enterprise Data via Autonomous Coding Agents

arXiv:2606.19319v2 Announce Type: replace-cross Abstract: Production data integration is bottlenecked by repeated, lossy handoffs between data owners, engineers, and analysts who must collaboratively

agentsarxiv-cs-ai

Industry

Data loss prevention gets a second act as AI rewrites an old security problem

Security vendors are rebuilding data loss prevention, or DLP, around contextual understanding rather than pattern matching — and AI-powered DLP is giving the category’s most stubborn unsolved problem

industrysiliconangle