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arXiv:2609.34063v1 Announce Type: new Abstract: Residual completion augments query-aware sparse attention by estimating the contribution of tokens omitted from the exact sparse computation. We ask whe

local-aiarxiv-cs-lg

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Counterfactual Attention Policy Distillation for Temporal Video Grounding

DGX agent

arXiv:2609.34581v1 Announce Type: new Abstract: Temporal video grounding is a key capability of advanced Multimodal Large Language Models (MLLMs) for the thorough understanding of video events, which

safetyarxiv-cs-cv

29 Sept 2026

Counterfactual Rollout Replay: Forkable Environments as Free Process Rewards for Software Engineering Agents

arXiv:2609.33875v1 Announce Type: cross Abstract: Outcome-only reinforcement learning gives software engineering (SWE) agents a terminal success signal but little direct guidance about intermediate de

Counterfactual Self-Evolving Agents for Evidence-Grounded Reasoning

arXiv:2609.32870v1 Announce Type: cross Abstract: Self-play proposer--solver methods improve reasoning by generating tasks and learning from verified solutions. However, for evidence-identifiable task

Counting on Thinking: Tracing Evidence Integration in Language Models

arXiv:2609.32932v1 Announce Type: new Abstract: Finite computational resources force a tradeoff between automatic System 1 processes and costly System 2 thinking. Large language models (LLMs) can spen

Applications

Coverage-aware Semantic Representation Learning for Underrepresented Visual Concepts

arXiv:2602.16917v2 Announce Type: replace Abstract: Modern vision models increasingly rely on rich semantic representations that extend beyond class labels to include descriptive concepts, attributes,

applicationsarxiv-cs-cv

Tutorials

CRF Loss is How Networks Should Learn Boundaries in Weakly Supervised Segmentation

arXiv:2609.34183v1 Announce Type: new Abstract: Weakly Supervised Semantic Segmentation (WSSS) learns pixel-level predictions from image-level tags. Recent work focuses on improving coarse CAMs extrac

tutorialsarxiv-cs-cv

Cross-Dataset Generalization of Bangladeshi Rice Leaf Disease Classifiers: Benchmark, Diagnosis, and Mitigation

arXiv:2609.31709v1 Announce Type: new Abstract: Cross-dataset transfer in rice leaf disease classification remains a significant challenge, with models trained on one image collection performing subst

Cross-Dataset Transfer and Unknown-Class Detection in Imbalanced SAR Ship Classification

arXiv:2609.31658v1 Announce Type: new Abstract: Ship classification from Synthetic Aperture Radar (SAR) imagery is a critical computer vision task, yet the robustness of models under deployment shifts

researcharxiv-cs-cv

Applications

Cross-Domain Few-Shot Writer Adaptation for Real-World Handwritten Mathematical Expression Recognition

arXiv:2609.32513v1 Announce Type: new Abstract: Handwritten mathematical expression recognition (HMER) refers to the task of recognizing and converting handwritten mathematics into a parsable markup l

applicationsarxiv-cs-cv

Cross-Material Support Transfer for Core-Loss Prediction Under Waveform Covariate Shift

arXiv:2609.31659v1 Announce Type: new Abstract: Power magnetic materials are characterized on the sinusoidal and triangular waveforms that excitation hardware conveniently produces, whereas deployed c

Cross-Modal Knowledge Distillation for Acoustic Pedestrian Detection

arXiv:2609.31785v1 Announce Type: cross Abstract: Audio-only pedestrian detection is attractive for urban sensing but limited by weak acoustic cues. An appealing strategy is cross-modal knowledge dist

Local Ai

Cross-Rollout Bellman Closure for Long-Horizon Agentic Reinforcement Learning

arXiv:2609.35082v1 Announce Type: new Abstract: Group-based reinforcement learning such as GRPO trains LLM agents by comparing rollouts sampled for each task, without a learned critic. In long-horizon

local-aiarxiv-cs-lg

cSVR: Convolutional Slice-to-Volume Reconstruction

arXiv:2601.07519v2 Announce Type: replace-cross Abstract: Unpredictable fetal motion during MRI scans can result in oblique 2D slices that are difficult to interpret and often leads to prolonged scan

researcharxiv-cs-cv

CT-OPD: Counterfactual Trace On-Policy Distillation for Diffusion Vision-Language Models

arXiv:2609.32781v1 Announce Type: new Abstract: Diffusion vision-language models generate answers by gradually resolving masked tokens, making accurate conditional prediction in partially resolved sta

CTP-FL: Common-Trajectory Gradient Prediction for Federated Learning

arXiv:2609.35130v1 Announce Type: new Abstract: Communication-efficient federated optimization commonly spends several gradient evaluations between server updates. Existing local-update methods use th

CueKFS: Agentic Cue-Driven Keyframe Selection for Long Video Understanding

arXiv:2609.31873v1 Announce Type: new Abstract: Keyframe selection (KFS) has long produced compact video summaries for browsing and retrieval, and representative frames for thumbnails. More recently,

agentsarxiv-cs-cv

Curating Merchant-Matching Training Data with Two Confidence-Gated Local LLM Judges

arXiv:2609.33878v1 Announce Type: cross Abstract: Merchant matching resolves a noisy payment descriptor to a retrieved merchant entity or returns no match. A key challenge in curating training labels

CyberWorld: World Models for Sample-Efficient Autonomous Cyber Defense

arXiv:2609.31893v1 Announce Type: new Abstract: Deep reinforcement learning has become a prominent approach to autonomous cyber defense. Existing methods are predominantly model-free and consequently

Tutorials

Cyclostationary Phase Conditioning for Medical Time Series Diffusion

arXiv:2609.34965v1 Announce Type: new Abstract: Many physiological time series, such as cardiac and brain recordings, exhibit cyclostationarity: their statistics vary periodically with an underlying c

tutorialsarxiv-cs-lg

D-GAP: Improving Out-of-Domain Robustness via Dataset-Agnostic and Gradient-Guided Augmentation in Frequency and Pixel Spaces

arXiv:2511.11286v3 Announce Type: replace Abstract: Out-of-domain (OOD) robustness is challenging to achieve in real-world computer vision, especially in unsupervised domain adaptation scenarios, wher

D-JEPA: Design-Recoverable JEPA Representation with Swappable Physics Decoders

arXiv:2609.33110v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) provide a framework for learning compact representations without directly reconstructing high-dimension

d-OPD: Future-Aware On-Policy Distillation for Block Diffusion Language Models

arXiv:2609.35362v1 Announce Type: new Abstract: Large language models (LLMs) typically generate text autoregressively (AR), predicting one token at a time. Block diffusion language models (dLLMs) inst

D^2-VLA: Dual-Memory Dual-Frequency Vision-Language-Action Model For Long Dynamic Manipulation

arXiv:2609.34792v1 Announce Type: new Abstract: Long-horizon manipulation requires robots to remember cues that are no longer in view while responding to moving objects. Yet vision-language-action (VL

Data Processing for Offline Evaluation in Recommender Systems: a Survey

arXiv:2609.31696v1 Announce Type: cross Abstract: Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on hist

DBCF: Dual-Branch Complementary Fusion of Foundation Models for Generalized Deepfake Detection

arXiv:2609.34720v1 Announce Type: new Abstract: As image generation and editing technologies have progressed substantially, facial forgeries pose significant challenges to privacy and public safety. D

DCEmbed: Scalable Optimization over Neural Surrogates

arXiv:2609.33879v1 Announce Type: cross Abstract: Neural surrogates can accelerate large-scale optimization by replacing expensive or intractable model components with efficient learned approximations

De-biasing Skeleton-based Action Recognition with Convex Hull Adaptive Shift

arXiv:2609.32454v1 Announce Type: new Abstract: Skeleton sequences can represent both individual actions and multi-entity interactions, encompassing human bodies, hands, objects, and robots. Existing

safetyarxiv-cs-cv

DEALS: Decentralized Expertise-Aware Load Serving for Multi-Agent LLM Systems

arXiv:2609.33768v1 Announce Type: new Abstract: Multi-agent systems (MAS) have recently emerged as an effective approach for coordinating large language model (LLM)-based agents to solve complex tasks

Decentralized Optimization with Cross-Coupled Mixed Affine Constraints

arXiv:2609.33021v1 Announce Type: cross Abstract: We study decentralized optimization with cross-coupled mixed affine constraints, where local and shared variables interact through two affine channels

DecFlowEdit: Self-Localized Flow-based Image Editing via Guidance Decoupling

arXiv:2609.34237v1 Announce Type: new Abstract: Flow-based image editing (FlowEdit) enables inversion-free semantic changes through the difference between source and target velocities. In this paper,

researcharxiv-cs-cv

Decision Readouts for Text-Mediated Video Anomaly Detection: An Exploratory Evaluation of Jev and Qwen

arXiv:2609.34180v1 Announce Type: cross Abstract: How much does the decision readout matter when video-derived textual evidence is held fixed? We evaluate Jev typed decisions and three Qwen readouts o

Decision-Sufficient State Representations: Measuring and Reducing Write-Time Regret

arXiv:2609.32805v1 Announce Type: cross Abstract: Long tasks produce more history than an LLM agent can hold in its context, and more than it uses reliably even when the history fits. A growing line o

Decoupling Token Roles in Autoregressive Pretraining

arXiv:2609.33405v1 Announce Type: new Abstract: Autoregressive pretraining increasingly draws on heterogeneous data, making it important to understand how a model learns from an individual token. The

Deep Epistemic Value Functions for Optimistic Exploration

arXiv:2609.35525v1 Announce Type: new Abstract: Principled exploration in reinforcement learning requires an agent to quantify its epistemic uncertainty and act to resolve it. Uncertainty over the val

Deep kernel hedging

arXiv:2609.34474v1 Announce Type: new Abstract: We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods. The he

Deep Learning Techniques for Phoneme Recognition in Italian Children' s Speech

arXiv:2609.33060v1 Announce Type: new Abstract: Speech therapists often face difficulties diagnosing impairments due to the lack of efficient tools for transcribing speech into the International Phone

Deep Reinforcement Learning for Equity Trading: Benchmarking Actor-Critic Methods with Forward Retraining

arXiv:2609.31870v1 Announce Type: new Abstract: Consistently profitable trading is difficult because equity markets are noisy, non-stationary, and only partially predictable from historical data. We b

Deep Weighted Bellman Residual Minimization for Q^* Estimation

arXiv:2609.34593v1 Announce Type: new Abstract: Off-policy evaluation is a foundational component of offline reinforcement learning, aiming to assess and optimize policy performance using pre-collecte

Defending at machine speed: Securing the public sector in the agentic era

model-releasesgoogle-cloud-ai

Over the last three decades in cybersecurity, I’ve witnessed major paradigm shifts — yet none match the velocity and complexity of today’s landscape. Attackers are now using AI to move at machine spee

DegreeSpar: Structured Degree Sparsity for Efficient Secure Transformer Inference

arXiv:2609.32204v1 Announce Type: cross Abstract: Secure Transformer inference protects sensitive inputs but incurs substantial cryptographic overhead, with nonlinear operations such as Softmax and Ge

DeltaSeek: Toward Active Perception in Evolving Construction Environments

arXiv:2609.33836v1 Announce Type: cross Abstract: Construction environments evolve continuously, causing large geometric changes that degrade static mapping and registration performance. This necessit

DeltaWAM: Change-Centric Visual Foresight via Delta Tokens for an Efficient World-Action Model

arXiv:2609.33177v1 Announce Type: cross Abstract: World-Action Models (WAMs) offer visual foresight for robotic manipulation, but pixel-space models repeatedly reconstruct entire future scenes, incurr

safetyarxiv-cs-cv

Demonstration-Free Success-Probability Reward Learning for Generalist Robot Policies

arXiv:2609.33653v1 Announce Type: cross Abstract: Reinforcement learning (RL) enables generalist robot policies to improve through trial-and-error interaction, yet its effectiveness is fundamentally c

Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion

arXiv:2510.04525v3 Announce Type: replace Abstract: Masked diffusion models have shown promising performance in generating high-quality samples in a wide range of domains, but accelerating their sampl

Denoising Multi-Robot Trajectories

arXiv:2609.35651v1 Announce Type: new Abstract: Multi-robot trajectory planning is a fundamental problem in multi-robot coordination but remains computationally challenging due to its nonconvex, multi

researcharxiv-cs-ro

Depot-Closed Multi-Component Construction for Neural Vehicle Routing

arXiv:2609.35066v1 Announce Type: new Abstract: Most neural constructive solvers for the vehicle routing problem (VRP) use route-by-route construction, extending one route until completion before star

Depth Any Seen: Which Surfaces and How Far?

arXiv:2609.32027v1 Announce Type: new Abstract: When several surfaces are visible along a ray, recovering visible 3D structure from one image requires jointly estimating their presence and metric dept