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NLP-Driven Knowledge Extraction and Thematic Classification of Translated Ancient Indian Medical Texts

arXiv:2608.28608v1 Announce Type: cross Abstract: Ancient Indian medical texts like Sushruta Samhita have extensive information on diseases, treatments, and surgical techniques. Yet, their ancient for

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nnMNet: Baseline for Martian Terrain Semantic Segmentation

DGX agent

arXiv:2608.29609v1 Announce Type: new Abstract: Semantic segmentation is a crucial task for understanding Mars, the most Earth-like planet in our solar system. However, it is challenging because the M

model-releasesarxiv-cs-cv

1 Sept 2026

No Detectable Change in Side-Level WER from Prompt-Level Context: A Preregistered Ablation on a Production Oral-History Corpus

model-releasesarxiv-cs-ai

arXiv:2608.28875v1 Announce Type: cross Abstract: Supplying context at inference time to a large multimodal model is an inexpensive lever for adapting speech transcription to a domain, and earlier res

No Equivariant Architecture Covers All Equivariant Attention

arXiv:2608.30417v1 Announce Type: new Abstract: We give a complete characterization of equivariant multi-head self-attention (MHSA): if an MHSA layer is equivariant to a symmetry group G, then G can o

NoisEasier: Test-Time Noise Optimization for Text-to-Video Generation

arXiv:2608.30194v1 Announce Type: new Abstract: Diffusion models have recently advanced text-to-video (T2V) generation, yet they still struggle with fine-grained compositional alignment, such as attri

safetyarxiv-cs-cv

Nonparametric Contextual Pricing and Inventory Learning under Censored Demand

arXiv:2608.30944v1 Announce Type: new Abstract: In online retailing, when a product sells out, a retailer often sees only the units sold, not how many customers would have bought it had inventory been

safetyarxiv-cs-lg

Normalized Low-Rank Adaptation

arXiv:2608.31036v1 Announce Type: new Abstract: While low-rank adaptation (LoRA) is widely used for parameter-efficient model adaptation, how to regularize its training dynamics for stable and effecti

Applications

Not All Fallbacks Are Failures: Understanding and Recovering from Fallbacks in Mobile Voice Assistants

arXiv:2608.30738v1 Announce Type: new Abstract: Robust understanding of user input is a core requirement for voice assistants deployed in real-world environments. In practice, these systems encounter

applicationsarxiv-cs-cl

Applications

Not All or None: Dynamic Construction of Target-aware Memory Graph for Conversational Stance Detection

arXiv:2608.29066v1 Announce Type: cross Abstract: Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more cha

applicationsarxiv-cs-ai

Not Safe for All: Auditing the Dialect Penalty in Text-to-Image Safety Pipelines

arXiv:2608.29589v1 Announce Type: new Abstract: Text-to-image (T2I) safety guardrails fail to generalize equitably to non-standard dialects. Evaluating 23,080 paired prompts across five English dialec

Not the Same Protector: Deployment-Dependent Protective Intervention in LLMs

arXiv:2608.29136v1 Announce Type: cross Abstract: We ask whether a model protects a user in the same way when that user speaks rather than types. Using a single distress vignette---a physical injury o

Not Your Typical Sycophant: The Elusive Nature of Sycophancy in Large Language Models

arXiv:2601.15436v3 Announce Type: replace Abstract: We propose a novel perspective for probing LLM sycophancy in a direct and neutral way, mitigating various forms of uncontrolled bias, noise, or mani

Null-Space Diffusion Restoration with Adaptive Uncertainty-Guided Fusion for Ultrasound Speckle Reduction

model-releasesarxiv-cs-cv

arXiv:2608.29820v1 Announce Type: new Abstract: Ultrasound B-mode imaging commonly suffers from speckle noise and artifacts, requiring a delicate balance between contrast, resolution, and preservation

NVE: A Separability and Coverage-Aware Internal Validation Metric for Biclustering

arXiv:2608.29045v1 Announce Type: new Abstract: Biclustering, or co-clustering, aims to discover coherent submatrices by grouping rows and columns of a data matrix simultaneously. This local two-dimen

researcharxiv-cs-lg

Hardware

NVIDIA and CrowdStrike Strengthen Agentic Cybersecurity Frontier

“We’re at an inflection point in cybersecurity,” Jensen Huang told a sold-out crowd at CrowdStrike’s Fal.Con 2026 in Las Vegas Tuesday. Attacks are now automated. Defense has to be, too. The NVIDIA fo

hardwarenvidia-blog

Hardware

Nvidia’s controversial DLSS 5 arrives September 3rd and requires serious GPU horsepower

Nvidia is officially launching DLSS 5 this week, following a divisive announcement in March where we likened the AI upscaling tech to a 'real-time generative AI filter for video games' and 'motion smo

hardwarethe-verge-ai

OASIS: Optimizing Attacker Sequences for Hard-Label Black-Box Text Attacks

arXiv:2608.29568v1 Announce Type: cross Abstract: Different attack methods follow different search trajectories, they succeed on different subsets of samples, whereas existing hard-label black-box tex

researcharxiv-cs-cl

ObjectSplat: Improving Mesh Fidelity and Interactivity for 3D Scenes via Object-Level Mesh Splatting

arXiv:2608.30423v1 Announce Type: cross Abstract: Splatting-based algorithms reconstruct photorealistic, real-time-renderable, and mesh-exportable 3D scenes from regular images, but they represent a s

OCR-Based Field Extraction for Archaeological Pottery Metadata: The CENTURIA Dataset

arXiv:2608.30616v1 Announce Type: new Abstract: Pottery is a primary source for reconstructing the chronological and economic dimensions of past societies. Archaeologists often document ceramic finds

researcharxiv-cs-cv

OCR-MetaReasoning Benchmark: Evaluating the Meta-Reasoning Ability of MLLMs in Text-Rich Image Understanding

arXiv:2608.30678v1 Announce Type: new Abstract: Text-rich image understanding requires multimodal large language models (MLLMs) to organize OCR (Optical Character Recognition)-grounded evidence across

Agents

Oculi: A Conversational Agentic Platform for Automated Credit Risk Analysis

arXiv:2608.28944v1 Announce Type: new Abstract: Credit risk analysis in financial institutions traditionally requires analysts to manually write SQL queries, run statistical computations, and build vi

agentsarxiv-cs-ai

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information

arXiv:2607.19313v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on diffic

Off-Manifold Refinement: Guiding Video Generators with a Frozen World Model

arXiv:2608.29904v1 Announce Type: new Abstract: Modern video generators routinely fail at physical dynamics: objects float, trajectories violate gravity, contacts vanish. Standard denoising and flow-m

researcharxiv-cs-cv

Off-Policy Evaluation for Semantic ID Recommenders: Does the Model's Own Code Hierarchy Help?

arXiv:2608.28905v1 Announce Type: new Abstract: Generative recommenders increasingly emit semantic IDs (SIDs): each item is a short sequence of hierarchical discrete codes from a residual quantizer, d

safetyarxiv-cs-lg

Local Ai

Ollama already support the Muse Code harness out of the box? You can try it with models via Ollama (local and cloud): ollama launch muse

Ollama already support the Muse Code harness out of the box? You can try it with models via Ollama (local and cloud): ollama launch muse Muse Code is out of beta and now built to handle bigger, more c

local-aiollama--x

Ollama’s Pro, Max, and Team plans now use transparent per-token pricing. Based on your feedback, every plan includes a monthly pool of usage…

Ollama’s Pro, Max, and Team plans now use transparent per-token pricing. Based on your feedback, every plan includes a monthly pool of usage credits. If you’re on an existing Pro, Max, or Team plan, y

model-releasesollama--x

OmniACBench: A Benchmark for Evaluating Context-Grounded Acoustic Control in Omni-Modal Models

arXiv:2603.23938v2 Announce Type: replace Abstract: Most testbeds for omni-modal models assess multimodal understanding via textual outputs, leaving it unclear whether these models can properly speak

On Adversarial Attacks In Acoustic Drone Localization

arXiv:2502.20325v3 Announce Type: replace-cross Abstract: Multi-rotor aerial autonomous vehicles (MAVs, more widely known as 'drones') have been generating increased interest in recent years due to th

safetyarxiv-cs-ro

On the Complexity of the Compatibility Problem for Succinctly Encoded Conditional Distributions

arXiv:2608.31120v1 Announce Type: new Abstract: The motivation for this paper is the investigation of the trade-offs implicit in probabilistic models used in machine learning. Models are often used to

researcharxiv-cs-lg

On the Design of Qwen3.8-Next Architecture: Evaluation, Efficiency, and Training Stability

arXiv:2608.30320v1 Announce Type: new Abstract: We describe the architecture and ablations of Qwen3.8-Flash-Next, a sparse mixture-of-experts model with 125B parameters, 6B activated per token, and ad

On the Instance Hardness as a Decision Criterion in TinyML Systems

arXiv:2608.29913v1 Announce Type: new Abstract: TinyML includes the implementation of machine learning on devices with limited memory and computing resources. With the development of technology, AI sy

On the Optimality of Kinship Naming: an Information-theoretic Approach

arXiv:2511.19120v2 Announce Type: replace-cross Abstract: The structure of naming systems in natural languages hinges on a trade-off between high informativeness and low complexity. Focusing on the do

On the Plasticity Collapse in Continual Machine Unlearning

model-releasesarxiv-cs-ai

arXiv:2608.29513v1 Announce Type: cross Abstract: Machine unlearning enables deep neural networks to selectively remove the influence of specific data in response to privacy and regulatory requirement

On the Prospects of Dynamic LLM Conversations in Software Development

arXiv:2608.30756v1 Announce Type: cross Abstract: Large language models (LLMs) have become an essential tool for assisting developers, yet we still lack knowledge on ways to effectively support their

On the Recoverability of Private Information Unlearning in Large Language Models

arXiv:2608.29943v1 Announce Type: cross Abstract: Large language models (LLMs) can memorize sensitive information, raising serious privacy concerns. Machine unlearning offers a potential solution to r

researcharxiv-cs-cl

On the Resilience of Text-to-Video Diffusion Models to Hardware Faults

arXiv:2608.29598v1 Announce Type: new Abstract: We present the first systematic study of the resilience of text-to-video (T2V) diffusion models under random hardware-level faults. While T2V models are

On the Role of MRI Sequences in Cross-Dataset Generalization for Brain Tumor Segmentation

arXiv:2608.29944v1 Announce Type: new Abstract: Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learni

researcharxiv-cs-cv

One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning

model-releasesarxiv-cs-cv

arXiv:2608.31096v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires a model to incrementally learn tasks that contain new classes without accessing earlier training data while pr

Tutorials

One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spread

arXiv:2608.30311v1 Announce Type: cross Abstract: Social media platforms increasingly use AI-based credibility indicators to help users judge misinformation. Unlike individual human-AI decision-making

tutorialsarxiv-cs-ai

One Capability or Many? Testing the Economic Validity of Frontier AI Evaluation

arXiv:2608.29420v1 Announce Type: new Abstract: Frontier-model leaderboards now rank systems based on economic benchmarks, tests of how well models carry out professional tasks from software engineeri

One note in three: a verified census of three deployed AI scribes, and the instrument that counted it

arXiv:2608.31017v1 Announce Type: cross Abstract: Ambient AI scribes draft clinical notes under the reassurance that a clinician signs every note. We audited three commercial AI scribes on the same 14

One Policy Is Enough: Single-Agent Reinforcement Learning Outperforms Tree Search for Chemistry Tool Learning

arXiv:2608.30952v1 Announce Type: cross Abstract: Chemistry questions often demand exact computation and database lookups that a language model cannot supply from its parameters, so it must reach for

Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance

arXiv:2608.30317v1 Announce Type: cross Abstract: Online dynamic origin-destination (OD) matrix estimation (DODE) calibrates time-dependent OD demand to reproduce observed link-flow trajectories. In o

OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques

model-releasesarxiv-cs-ai

arXiv:2608.31137v1 Announce Type: new Abstract: Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural aligners to knowledge graph embedding

Agents

Ontology-Guided Multi-Agent Extraction of Evaluation Objects from Academic Review Texts: Evidence from Chinese Library and Information Science

arXiv:2608.29526v1 Announce Type: new Abstract: Academic reviews, scholarly commentaries, and book reviews serve as sources of evaluative statements about theories, methods, literature, institutions,

agentsarxiv-cs-cl

OPAL: Orthonormal Prototype Alignment Learning for Interpretable Image Classification

arXiv:2608.30003v1 Announce Type: new Abstract: Prototypical part-based models provide explainable predictions by comparing input regions to learned prototypes. However, current approaches are burdene

safetyarxiv-cs-cv

Open-Set Cattle Muzzle Identification: A Leakage-Controlled Benchmark and Evaluation Protocol

model-releasesarxiv-cs-cv

arXiv:2608.28663v1 Announce Type: new Abstract: Reliable individual cattle identification supports disease surveillance, vaccination records, breeding management, and livestock insurance. Although the

Agents

Open-Source Autonomous Driving System Analysis and Multi-Disciplinary Hardware-in-the-Loop Research Paradigm with Reinforcement-Learning Testing and Large Language Models

arXiv:2608.30179v1 Announce Type: cross Abstract: Open-source autonomous driving systems provide an inspectable software foundation for intelligent vehicle research. Under real-vehicle deployment cond

agentsarxiv-cs-ro