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Speculative Correction: Draft-then-Refine Decoding for Diffusion Language Models

arXiv:2608.02625v1 Announce Type: cross Abstract: Diffusion language models (DLMs) can revise tokens bidirectionally, but standard decoding procedures often adapt them to left-to-right generation by p

local-aiarxiv-cs-ai

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Research

Speech LLMs in Low-Resource Scenarios: Data Volume Requirements and the Impact of Pretraining on High-Resource Languages

DGX agent

arXiv:2508.05149v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource languages, reaching state-of-the-art perf

researcharxiv-cs-ai

5 Aug 2026

Sphere Retraction Normalizations

arXiv:2608.02668v1 Announce Type: cross Abstract: Residual connections are the de facto mechanism for training deep neural networks stably. Geodesic Normalization (GeoNorm) recasts them on a Riemannia

SpreadMark: Robust Image Watermarking via Spread-Spectrum Embedding

arXiv:2608.03165v1 Announce Type: cross Abstract: Invisible image watermarks are increasingly used for deepfake detection and provenance tracking, where they must survive not only incidental distortio

SRAP: SVD-Refined Adversarial Perturbations for Imperceptible Face-Swap Defense

arXiv:2608.03395v1 Announce Type: new Abstract: Deepfake technologies pose increasing threats to facial privacy and identity security, motivating proactive defenses that protect facial images before m

Standalone DINOv3 for Training-Free Open-Vocabulary Semantic Segmentation in Remote Sensing

arXiv:2608.03023v1 Announce Type: cross Abstract: Remote sensing semantic segmentation is hindered by costly pixel-level annotations, motivating training-free open-vocabulary methods. Recently, the re

State Propagation Also Satisfies: A Complex-Valued State-Space Model for Deterministic State Tracking

arXiv:2608.03425v1 Announce Type: new Abstract: Transformer-based architectures have dominated sequence modeling, largely due to the expressive power of attention mechanisms. However, for a class of d

States Hidden in Hidden States: Implicit Discrete State Representations Emerge in LLMs' Hidden States

arXiv:2407.11421v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit emergent abilities that may reveal aspects of their internal mechanisms. We study one such capability: directly

Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study

arXiv:2608.02811v1 Announce Type: new Abstract: Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty

safetyarxiv-cs-ro

Agents

Steganalysis of Adaptive Covert Collusion in Tool-Using Agent Populations: A Black-Box, Cross-Principal Approach

arXiv:2608.02698v1 Announce Type: cross Abstract: Tool-using agents built on large language models (LLMs) are increasingly deployed not by a single operator but by many, side by side on shared infrast

agentsarxiv-cs-ai

StereoVGGT: A Training-Free Visual Geometry Transformer for Stereo Vision

model-releasesarxiv-cs-cv

arXiv:2603.29368v2 Announce Type: replace Abstract: Driven by the advancement of 3D devices, stereo vision tasks including stereo matching and stereo conversion have emerged as a critical research fro

Stiffness Copilot: An Impedance Policy for Contact-Rich Teleoperation

arXiv:2603.14068v2 Announce Type: replace Abstract: In teleoperation of contact-rich manipulation tasks, selecting robot impedance is critical but difficult. The robot must be compliant to avoid damag

safetyarxiv-cs-ro

Stochastic Multiple Shooting Trajectory Optimization via Sequential Local Policy Evaluation

arXiv:2608.03978v1 Announce Type: new Abstract: Stochastic single shooting trajectory optimization methods such as Model Predictive Path Integral control (MPPI) have been widely adopted in robotics du

local-aiarxiv-cs-ro

Stochastic Saddle Avoidance Beyond Unit Excitation and Smoothness: A Pathwise Lyapunov-Perron Framework

arXiv:2608.03001v1 Announce Type: cross Abstract: Unit excitation (UE) is a common assumption in stochastic saddle avoidance: the stochastic error must have a uniformly positive component along every

researcharxiv-cs-lg

Stop Replacing Noise with Noise: Two-Source Reliability Assessment for Label Correction and Sample Reweighting in Label-Noise Learning

arXiv:2608.03432v1 Announce Type: cross Abstract: Refurbishment-based noisy-label learning mixes an observed label with a model-derived pseudo target, typically using one sample-wise cleanliness score

applicationsarxiv-cs-cv

STREAM-VAE: Dual-Path Routing for Slow and Fast Dynamics in Vehicle Telemetry Anomaly Detection

arXiv:2511.15339v3 Announce Type: replace-cross Abstract: Automotive telemetry data exhibits slow drifts and fast spikes, often within the same sequence, making reliable anomaly detection challenging.

StreamDAM: Presence-Aware Memory for Real-Time Streaming Video Object Segmentation

arXiv:2608.03912v1 Announce Type: new Abstract: Quality-tier video object segmentation (VOS) trackers such as DAM4SAM top accuracy leaderboards, but they are measured offline, one frame at a time with

safetyarxiv-cs-cv

string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithms

arXiv:2608.03984v1 Announce Type: new Abstract: We present string2string Studio, an interactive in-browser platform for string-to-string analysis across natural language processing, computational biol

safetyarxiv-cs-cl

Strong bounds for large-scale Minimum Sum-of-Squares Clustering

arXiv:2502.08397v3 Announce Type: replace-cross Abstract: Clustering is a fundamental technique in data analysis and machine learning, used to group similar data points together. Among various cluster

researcharxiv-cs-lg

Structure-Aware Robust Fine-Tuning: Defending Vision-Language-Action Robots Against Physical Attention Hijacking

arXiv:2608.03231v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies promise general robotic manipulation, but their robustness against physical-world attacks remains fragile. In pa

local-aiarxiv-cs-ai

Stuck on 'A': Diagnosing and Repairing Interface Injury in Attention-to-KDA Linearization of a 0.6B Language Model

model-releasesarxiv-cs-cl

arXiv:2608.02689v1 Announce Type: new Abstract: We convert 21 of 28 full-attention layers of Qwen3-0.6B-Base into KDA (Kimi Delta Attention) linear-attention layers on a single consumer-grade GPU budg

Agents

Studying, Identifying, and Fixing Hidden Technical Debt in AI-Intensive Cyber-Physical Systems

arXiv:2608.02638v1 Announce Type: cross Abstract: Artificial Intelligence (AI) components are increasingly pervasive in several software systems, including Cyber-Physical Systems (CPSs). AI-CPS are us

agentsarxiv-cs-ai

StuPASE: Towards Low-Hallucination Studio-Quality Generative Speech Enhancement

arXiv:2603.09234v2 Announce Type: cross Abstract: Achieving high perceptual quality without hallucination remains a challenge in generative speech enhancement (SE). A representative approach, PASE, is

Tutorials

Style-Aware Gloss Control for Generative Non-Photorealistic Rendering

arXiv:2602.16611v3 Announce Type: replace-cross Abstract: Humans can infer material characteristics of objects from their visual appearance, and this ability extends to artistic depictions, where simi

tutorialsarxiv-cs-cv

Stylometric Defenses Against Author Impersonation in Software Repositories

arXiv:2608.02695v1 Announce Type: cross Abstract: Software supply-chain attacks increasingly exploit an identity gap where compromised maintainer accounts authorize malicious changes. This work evalua

applicationsarxiv-cs-lg

Subjective Risk Decomposition: A New View for Uncertainty Quantification

arXiv:2607.15196v2 Announce Type: replace-cross Abstract: We present a novel viewpoint for uncertainty quantification. Uncertainty measures are not primitives, in need of axioms and argumentation, but

Suffix-Constrained Greedy Search Algorithms for Causal Language Models

arXiv:2603.01243v2 Announce Type: replace Abstract: Large language models (LLMs) are powerful tools that have found applications beyond human-machine interfaces and chatbots. Beside free-form generati

Surface Keypoint Representation for Multi-Object and Articulated Human-Object Interaction Generation

arXiv:2608.03158v1 Announce Type: new Abstract: Daily activities require humans to coordinate whole-body motion with the motion of surrounding objects. Despite recent progress in human-object interact

Surrogate Substitution Preserves PHI Detectability: A Multi-Detector Equivalence Study

arXiv:2608.03172v1 Announce Type: new Abstract: Structure-preserving de-identification replaces protected health information (PHI) with realistic same-type surrogates -- 'Anna S.' becomes 'Maria S.',

SUV: Future Scene Understanding as Video Generation for End-to-End Driving

model-releasesarxiv-cs-cv

arXiv:2608.03084v1 Announce Type: new Abstract: End-to-end driving requires a coherent understanding of future scenes, yet existing methods model these scenes using task-specific heads and output form

SynEnergy: Anomaly Semantic-Guided Diffusion for Synthetic Energy Data Generation

arXiv:2608.03087v1 Announce Type: cross Abstract: Fine-grained energy consumption data are essential for applications such as demand forecasting, demand response planning, and grid reliability assessm

applicationsarxiv-cs-ai

T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models

arXiv:2512.23953v2 Announce Type: replace Abstract: The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent video

safetyarxiv-cs-cv

TabletCraft: Bridging a 4,000-Year Cultural Gap with Bidirectional Akkadian NMT and Cuneiform Rendering

arXiv:2608.02609v1 Announce Type: new Abstract: Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, le

TACT: Taxonomy-Aligned Post-Training for Pedagogically Adaptive English Tutoring

arXiv:2608.03952v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to provide conversational practice for English-as-a-second-language (ESL) learners. Effective ESL tut

Taming the Implicit: Dual-Channel Risk-Aware Reinforcement Fine-Tuning for Continual Multimodal Post-Training

arXiv:2608.03660v1 Announce Type: new Abstract: Reinforcement fine-tuning (RFT) is widely believed to inherently resist catastrophic forgetting in continual post-training of multimodal large language

Target-Aligned Fusion for Decision-Sequence Learning under Dynamics Shift

arXiv:2511.09173v3 Announce Type: replace-cross Abstract: External trajectories can improve offline decision-sequence learning, but dynamics shift may make some source subsequences inconsistent with t

local-aiarxiv-cs-ai

Target-Aware Early Stage Ranking

arXiv:2511.21095v2 Announce Type: replace Abstract: Early Stage Ranking (ESR) in large-scale recommendation systems is dominated by ''user--item decoupling'' Two Tower architectures, which scale effic

applicationsarxiv-cs-lg

TARL: Transaction-Aware Reliable Ledgers for Executable Memory Management in Long-Term Agents

arXiv:2608.03699v1 Announce Type: new Abstract: Persistent memory helps long-term agents retain knowledge, yet a single update error can repeatedly distort future retrieval and reasoning. Most existin

Task-Oriented Candidate-Latent Feedback for Coarse-to-Fine Sensing in Distributed OFDM-ISAC Networks

model-releasesarxiv-cs-lg

arXiv:2608.03319v1 Announce Type: cross Abstract: Future integrated sensing and communication (ISAC) architectures separate the sensing entity (SE) that acquires measurements from the sensing function

Tutorials

TaskPress: Query-Agnostic KV Cache Compression via Task-Guided Pruning

arXiv:2608.03276v1 Announce Type: new Abstract: Long-context inference with large language models is constrained by the linear growth of the key-value cache to sequence length. While pruning offers mi

tutorialsarxiv-cs-ai

TASQ: Temporal-Adaptive Bit Sparsification Quantization for Diffusion Models

arXiv:2608.03057v1 Announce Type: new Abstract: Static quantization assigns one weight precision to every denoising step. To preserve quality, that precision must accommodate the most quantization-sen

TDVR: Joint Text Disambiguation and Viewpoint Reasoning for Zero-Shot 3D Visual Grounding

arXiv:2608.03763v1 Announce Type: new Abstract: Zero-shot 3D visual grounding aims to localize specific objects based on textual descriptions and 3D visual input. However, the effectiveness of existin

local-aiarxiv-cs-cv

Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores

arXiv:2608.02985v1 Announce Type: cross Abstract: The standard check for contamination in LLM backtests is simple: compare scores before and after the training cutoff. We show this check is uninformat

Test Time Adaptation Methods for Point Cloud Registration in Laparoscopic Surgery

arXiv:2608.02883v1 Announce Type: new Abstract: 3D point cloud registration in laparoscopic surgery estimates the transformation between an intraoperative organ reconstructed from video and its preope

safetyarxiv-cs-cv

Test-Time Augmentation for Tabular-to-Image Classifiers under Distribution Shifts

model-releasesarxiv-cs-cv

arXiv:2608.03557v1 Announce Type: new Abstract: Tabular-to-image methods that convert tabular data into visual representations have emerged as a novel paradigm for leveraging the high performance of d

Test-Time Scaling for Safe Text-Guided Image Generation via Intermediate Clean Estimates

arXiv:2608.03284v1 Announce Type: cross Abstract: Ensuring safety and policy compliance in text-to-image diffusion models remains a critical challenge, as benign or adversarial prompts can often elici

safetyarxiv-cs-ai

Test-Time Scaling in Reasoning LLMs: Inference Regimes, Evaluation, and Reproducibility

arXiv:2608.04001v1 Announce Type: cross Abstract: Large language models can solve substantially harder reasoning problems with more inference-time compute. The term 'test-time scaling,' however, now c

The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems

arXiv:2608.03214v1 Announce Type: new Abstract: Large language models have transformed artificial intelligence from isolated prediction services into components of long-running, distributed systems th

safetyarxiv-cs-ai