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Trust-Based Incentive Mechanisms in Semi-Decentralized Federated Learning Systems

arXiv:2602.08290v2 Announce Type: replace-cross Abstract: In federated learning (FL), decentralized model training allows multi-ple participants to collaboratively improve a shared machine learning mo

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TruthLens: Object Hallucination Detection via Self-Evaluating Truthfulness Scores in LVLMs

DGX agent

arXiv:2608.05616v1 Announce Type: new Abstract: Despite the remarkable progress of large vision language models (LVLMs), object hallucination remains a fundamental challenge that hinders their trustwo

researcharxiv-cs-cv

7 Aug 2026

TRW: TRACE-RealWorld---An Auditable Consistency Contract for World Models as Materialized Views

arXiv:2607.21910v2 Announce Type: replace Abstract: World models let agents plan against predicted physical state, but that state drifts; re-observation is costly and delayed, and repair can fail. We

local-aiarxiv-cs-ai

TS-RAG: Retrieval Augmented Generation for Time Series Forecasting

arXiv:2608.06223v1 Announce Type: new Abstract: While deep learning models, particularly transformer-based architectures, have shown impressive performance in time series forecasting, the application

Turing's Frist Imitation Game: Design Concepts and a Human-Approximates-Machine Reading

arXiv:2608.05558v1 Announce Type: cross Abstract: This paper examines Turing's 1948 report, 'Intelligent Machinery', as an important conceptual source for the later imitation games. Its first contribu

Tytan: Interactive Neurosymbolic Construction of Analytic Semantic Schemas from Relational Data

arXiv:2608.06331v1 Announce Type: cross Abstract: From natural-language query interfaces to automated report generation, data analysis tools need a description of the data: the real-world entities it

Applications

Uncertainty-Aware World Model for Aerial Image-Goal Navigation

arXiv:2608.05597v1 Announce Type: new Abstract: Aerial image-goal navigation requires an unmanned aerial vehicle (UAV) to reach a target location specified by a goal image. Existing world-model-based

applicationsarxiv-cs-cv

Unified Agent: Managing Interactions across Devices

arXiv:2608.05729v1 Announce Type: new Abstract: As capabilities rapidly increase, AI agents can move from running inside one app to acting across a user's devices over time. Yet existing agent systems

Unified Planning-Learning Framework for Robust UUV Navigation Under Partial Observability

arXiv:2608.05365v1 Announce Type: new Abstract: This paper presents an observation-only autonomy framework for Unmanned Underwater Vehicles (UUVs) navigation in dynamic underwater environments that in

local-aiarxiv-cs-ro

Universal Concept Disruption for SAM3 Image Segmentation

arXiv:2608.05983v1 Announce Type: new Abstract: SAM3 extends promptable segmentation from geometry-driven mask prediction to open-vocabulary concept segmentation, where a text-conditioned grounding mo

Universal Pathologies, Conditional Consequences: A Triple-Robustness Analysis of RAG for Multi-Hop Traceability

arXiv:2608.05153v1 Announce Type: cross Abstract: GraphRAG underperforms vector RAG on citation precision in many reports, but where and why have remained corpus-bound. We present a triple-robustness

UniVVT: A Unified End-to-End Framework for High-Fidelity Video Virtual Try-on

arXiv:2608.05745v1 Announce Type: cross Abstract: Video Virtual Try-On (VVT) synthesizes a video of a person wearing a target garment while preserving identity, motion, and scene dynamics. Dominant ap

UQ-Loc: Uncertainty-Aware LiDAR Scene Coordinate Regression

arXiv:2608.06307v1 Announce Type: new Abstract: LiDAR-based Scene Coordinate Regression (SCR) maps point clouds directly to 3D scene coordinates, enabling precise 6-DoF localisation without explicit m

local-aiarxiv-cs-cv

URNet: A Unified Reparameterized Network for Efficient RGB-D Semantic Segmentation

arXiv:2608.05671v1 Announce Type: new Abstract: Previous RGB-D semantic segmentation methods commonly employ dual encoders to separately process RGB and depth inputs, followed by dedicated modules for

Velocity- and Regime-Aware Detection of Intraday Options Market Manipulation, with Explainable Attribution

arXiv:2608.05373v1 Announce Type: cross Abstract: Intraday market manipulation is hard to detect because its footprint is brief, buried in millions of quotes, and statistically similar to ordinary vol

researcharxiv-cs-lg

Verifiable Regularity Criterion for Conditional Expectation Operators and Conditional Mean Embeddings with Applications to Nonparametric Regression, Bayesian Inverse Problems, and Koopman Operators

arXiv:2608.06155v1 Announce Type: cross Abstract: Conditional expectation operators (CEOs) and their associated conditional mean embeddings (CMEs) play a central role across applied mathematics and ma

researcharxiv-cs-lg

Versatile Video Representation via Feed-Forward 2D Gaussian Splatting Tokenization

arXiv:2508.11183v2 Announce Type: replace Abstract: Recent video representation methods that rely on fixed-grid, patch-wise tokenization often exhibit limited versatility.Spatially, uniformly allocati

Vibe Compiler: A Research-Logic Synthesis Tool That Runs without Prompt Engineering -Toward Enhancing Metacognition for Sustaining Agency in the Age of Generative AI-

arXiv:2608.05545v1 Announce Type: cross Abstract: Generative AI used as a capable servant has greatly accelerated intellectual work, but it also risks eroding human epistemic agency by encouraging unc

VideoArgus: Agentic Rubric-Grounded Unified Evaluation for Video Generation and Editing

arXiv:2608.05485v1 Announce Type: new Abstract: Evaluating generated videos remains challenging because existing benchmarks rely on fixed evaluation content, cover only a subset of generation and edit

VIDP: Variable Impedance Diffusion Policy for Compliant Robot Manipulation from Diverse Demonstrations

arXiv:2608.06210v1 Announce Type: new Abstract: Contact-rich manipulation requires precise tracking and mechanical compliance, where variable impedance control can improve robustness in task success,

safetyarxiv-cs-ro

ViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion

arXiv:2608.05833v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge

Visual Grounding in Zero-Shot Vision-Language Control

arXiv:2608.06154v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used as zero-shot controllers, but successful trajectories do not necessarily show that decisions are g

Visual Intention Grounding for Egocentric Assistants

arXiv:2504.13621v2 Announce Type: replace Abstract: Visual grounding associates textual descriptions with objects in an image. Conventional methods target third-person image inputs and named object qu

Tutorials

VLAff: Vision-Language-Affordance Model for Unified Actionable Affordances

arXiv:2608.05215v1 Announce Type: cross Abstract: Learning manipulation skills from human videos is promising for scalable robot learning. However, the embodiment mismatch between humans and robots ma

tutorialsarxiv-cs-cv

Applications

VLMs for Videogame Data Annotation

arXiv:2608.05949v1 Announce Type: new Abstract: Vision Language Models (VLMs) and Artificial Intelligence (AI) agents have revolutionized how engineers approach complex problems in real-world applicat

applicationsarxiv-cs-ai

Vorch-Director: Interactive World Story Model via Noise-Aware Error Rectification

arXiv:2608.05776v1 Announce Type: new Abstract: Autoregressive continuation provides a natural path toward minute-scale audio-visual generation by repeatedly extending a short-window generator conditi

Vorch-IR: Long-Form Unified Multimodal Identity Replacement Video Generation

arXiv:2608.05648v1 Announce Type: new Abstract: Video identity replacement seeks to transfer the identities of one or more subjects while preserving the motion, expressions, and temporal structure of

Vorch-Omni: Multi-Task Orchestration of Sight and Sound

arXiv:2608.05803v1 Announce Type: new Abstract: Recent advances in generative video modeling have enabled diverse generation, reference-based synthesis, extension, and editing, but existing approaches

Vorch-Streamer: Extending Human Audio-Visual Generation to Real-Time Long-Form Streaming

arXiv:2608.05663v1 Announce Type: new Abstract: Real-time long-form avatar audio--video generation requires causal, continuous synthesis while maintaining audiovisual synchronization and visual consis

local-aiarxiv-cs-cv

VSMP-IMU: Video-Grounded Semantic Motion Programs for Sensor-Aware Synthetic IMU Generation

arXiv:2608.05782v1 Announce Type: new Abstract: Wearable human activity recognition (HAR) is often limited by the scarcity of labeled sensor data, especially in low-resource, class-imbalanced, and sub

Wan-Animate-2: Pushing the Application Boundaries of Character Animation

arXiv:2608.06009v1 Announce Type: new Abstract: Character image animation remains a foundational yet challenging task in computer vision. Existing approaches can be broadly categorized into three para

What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations)

arXiv:2608.06202v1 Announce Type: cross Abstract: Large language model (LLM) benchmark evaluations are routinely used to support claims about model safety, reliability, and deployment readiness. Yet m

What Drives Test-Time Adaptation for CLIP? A Controlled Empirical Study from an Update Perspective

arXiv:2606.14299v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) such as CLIP have become a standard backbone for open-vocabulary recognition, yet their zero-shot predictions remain v

When Agentic AI Meets Integrated Sensing and Communication

arXiv:2608.05792v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is transforming Integrated Sensing and Communication (ISAC) from a function-oriented physical-layer technology into

agentsarxiv-cs-ai

When Do Corrective Features Help? An Agent for Corrective Feature Discovery on Black-Box Forecasters

arXiv:2608.05207v1 Announce Type: new Abstract: Frozen pretrained forecasters often fail in structured, recurring ways that are costly to repair through fine-tuning. We study corrective feature discov

agentsarxiv-cs-lg

When Do Prompt-Side Agent Playbooks Transfer? Accuracy, Cost, and Runtime Shift in Agent Deployment

arXiv:2608.05778v1 Announce Type: new Abstract: Prompt-side playbooks can improve tool-using language agents without retraining, but their portability beyond the source setting is unclear. We study fr

agentsarxiv-cs-ai

When Does Consensus Mean Correctness? Measuring the Agreement-Accuracy Coupling with Semantics-Preserving Re-Rendering

arXiv:2608.05670v1 Announce Type: new Abstract: A model's agreement across perturbed inputs is used both as a label-free reliability signal and as a self-training target, on the premise that agreement

local-aiarxiv-cs-lg

When Drafts Evolve: Speculative Decoding Meets Online Learning

arXiv:2603.12617v2 Announce Type: replace-cross Abstract: Speculative decoding has emerged as a widely adopted paradigm for accelerating large language model inference, where a lightweight draft model

When Experience Becomes Instruction: Trajectory Poisoning in Self-Evolving Agent Skill Systems

arXiv:2608.05563v1 Announce Type: cross Abstract: Self-evolving skill (SES) systems distill agent trajectories into persistent skills, allowing untrusted experience to become trusted instruction. We i

agentsarxiv-cs-ai

When History Lies: Evaluating and Improving Tool Use under Misleading Multi-Turn Histories

arXiv:2608.06057v1 Announce Type: new Abstract: Tool-calling agents infer task state from accumulated dialogue and tool traces. In persistent interactions, however, historical traces may remain struct

When Privileged Guidance Misaligns: State-Matched Routing and Contextualized Self-Distillation for Multi-Turn Agents

arXiv:2608.05219v1 Announce Type: new Abstract: Privileged on-policy distillation provides dense supervision for multi-turn agents by allowing a synchronized teacher to re-score the student's response

When Self-Evolution Backfires: Pre-Commit Gating against Skill Contamination in LLM Agents

arXiv:2608.05810v1 Announce Type: new Abstract: Self-evolving agents accumulate capability by distilling reusable skills from their execution trajectories, but we find this process is not monotonic: p

Where Models Converge and Humans Diverge: A Coverage Framework for Distributional Pluralism in Open-Ended Generation

arXiv:2608.05576v1 Announce Type: new Abstract: When a large language model (LLM) writes Harry Potter fanfiction, it reliably produces fundamental elements of the Hogwarts universe, such as recognizab

researcharxiv-cs-cl

Where Privacy Risk Lives in English-Source Multilingual RAG: A Stage-Decomposed Audit Across Five Query Languages

model-releasesarxiv-cs-cl

arXiv:2608.05163v1 Announce Type: new Abstract: A common assumption holds that switching to a non-English language makes a multilingual RAG system easier to attack for personal information. We test th

Who Checks the Citations? Benchmarking Legal Hallucination Detection

model-releasesarxiv-cs-cl

arXiv:2606.21155v2 Announce Type: replace Abstract: Attorneys, judges, and pro se filers increasingly use AI to draft legal documents, yet these tools frequently fabricate citations. Despite predictio

Who Gets Access? Global Region and Academic Status Bias in AI-Generated Academic Gatekeeping Scenarios

arXiv:2608.05178v1 Announce Type: cross Abstract: Equitable access to scientific knowledge often depends on informal gatekeeping decisions, particularly when resources such as paywalled articles, data

Why the Third Axis Is Freedom

arXiv:2608.05423v1 Announce Type: cross Abstract: In generative training, a model produces an output and is penalised for its difference from an example. With one output per comparison, a model that p

Woodpecker Distillation: Weak Models Diagnose Reasoning Bugs in Strong Models

arXiv:2608.05168v1 Announce Type: new Abstract: Large language models often fail on reasoning tasks despite possessing the capability to solve them. We argue that many such failures arise from localiz

local-aiarxiv-cs-ai