Search: “framework”

FakeI2V-Bench: Benchmarking the Applicability of Image-level Deepfake Detectors for Deepfake Video Detection

arXiv:2608.03096v1 Announce Type: cross Abstract: Recent advances in video generation models have significantly intensified the deepfake threat, yet the current deepfake video detection benchmarks rem

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Safety

Fast Object Removal Attacks on Safety-Critical Video-based Perception Systems

DGX agent

arXiv:2608.02806v1 Announce Type: cross Abstract: By leveraging data from video-based perception systems, intelligent transportation systems (ITS) support safety-critical applications that improve roa

safetyarxiv-cs-cv

5 Aug 2026

FLARE: Few-shot Learning-based Adaptive Reflective Engine

model-releasesarxiv-cs-cl

arXiv:2608.02919v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in complex, compound AI systems where performance hinges on the quality of prompts. Recent state-

FlowForm: Synergizing Fluid Physics with Topological Consistency for Satellite Flood Synthesis

arXiv:2608.03822v1 Announce Type: cross Abstract: Developing robust flood assessment models requires high-quality paired satellite imagery, yet such data remain scarce for flood-specific image generat

Formal Verification of Agentic Systems over Operational Data

arXiv:2608.03609v1 Announce Type: new Abstract: Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world workflows where they act on persistent operational data.

FreqAdapt: Frequency-Adaptive Processing for RAW Object Detection

arXiv:2608.03385v1 Announce Type: new Abstract: Existing object detection methods predominantly utilize sRGB inputs, which are compressed from RAW sensor data using Image Signal Processors (ISP) origi

From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model

arXiv:2508.00955v3 Announce Type: replace-cross Abstract: Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive

From Routes to Steps: Separating Semantic Progress from Local Execution in Vision-and-Language Navigation

arXiv:2608.03143v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) requires an agent to follow a route-level instruction by executing its constituent steps from egocentric visual obs

safetyarxiv-cs-cv

GENESIS: Towards Explainable Causal Discovery

arXiv:2608.03868v1 Announce Type: cross Abstract: Causal Discovery (CD) from observational data faces two fundamental challenges. First, purely statistical methods often lack the power to resolve stru

Applications

GeoMAR: Unleashing Geometrically Aligned Features for Masked Autoregressive Blind Face Restoration

arXiv:2608.03923v1 Announce Type: new Abstract: Codebook-based blind face restoration (BFR) often suffers from ambiguous conditioning features and a fragile prediction mechanism under severe degradati

applicationsarxiv-cs-cv

Geospatial-Prior Guidance for 3D Semantic Scene Completion

arXiv:2608.03618v1 Announce Type: new Abstract: Inferring complete 3D geometry and semantics from onboard images remains challenging because occlusions and restricted fields of view leave large scene

Getting the Parameters Right: A Difficulty-Graded Benchmark and Probe-Guided Training for LLM Tool Calls

arXiv:2608.03071v1 Announce Type: new Abstract: Large language model agents derive much of their capability from tool use. Existing research on tool use has largely focused on selecting the right tool

GLOBE: Trajectory-Aligned Gradient Matching with Structured SparseOptimization for Coreset Selection

arXiv:2608.02690v1 Announce Type: new Abstract: On-device training of deep neural networks is fundamentally constrained by the computational and memory costs of large-scale datasets. Coreset selection

local-aiarxiv-cs-lg

GORDON: Graph-based Object-centric Rewards for Decomposition of Long-Horizon Manipulation

arXiv:2608.03753v1 Announce Type: new Abstract: Learning long-horizon manipulation skills with reinforcement learning remains challenging due to the complexity of reward design, the limited guidance o

safetyarxiv-cs-ro

GSTEP: Global Spatio-Temporal Density-Driven Visual Token Pruning for Efficient Video Large Language Models

arXiv:2608.03083v1 Announce Type: cross Abstract: Video large language models (VideoLLMs) achieve strong video understanding performance, but their inference remains expensive due to the large number

local-aiarxiv-cs-cl

GUI-Lens: Coarse-to-Fine Cropping for GUI Grounding with General-Purpose VLMs

arXiv:2608.03270v1 Announce Type: cross Abstract: GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resol

HERO: Hierarchical Evidential Reasoning Optimization for Radiology Report Generation via Reason-then-Summarize

arXiv:2601.03321v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have substantially advanced Radiology Report Generation (RRG), yet aligning them through reinforcemen

Hi-TTRL: Regulating Consensus with Hints for Test-Time Reinforcement Learning

arXiv:2608.03545v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) improves the reasoning capabilities of large language models without labeled data by updating the policy with ps

safetyarxiv-cs-cl

How Many Labels Are Enough? ALDA: Active Learning Deployment Advisor for Medical Image Classification

arXiv:2608.03511v1 Announce Type: cross Abstract: Active learning (AL) promises to reduce the cost of medical imaging projects by lowering the number of clinical labels required. However, practical de

HyperAgent: Planning and Acting over Tool-Schema Hypergraphs for Tool-Use LLM Agents

arXiv:2608.02650v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external tools to complete complex real-world tasks. However, reliable tool-use planning remains

Hypercubes, Hyperplanes, and Constraint-Induced Complexity Collapse in Atomic Concept Learning

arXiv:2608.02930v1 Announce Type: new Abstract: We revisit higher-arity atomic concept learning through the geometry of hypercubes and hyperplanes of ground instances. Our starting point is the observ

HyperFL: Query-Adaptive Representation Learning for Software Fault Localization

arXiv:2608.02967v1 Announce Type: cross Abstract: Software fault localization identifies the code locations responsible for reported issues and is a fundamental step toward automated debugging and pro

ICO: Enhancing Semantic-Shift Jailbreaks via Iterative Context Optimization

arXiv:2608.03210v1 Announce Type: new Abstract: Foundation models have achieved remarkable success across diverse tasks, but they remain vulnerable. To investigate such vulnerabilities, semantic-shift

safetyarxiv-cs-cl

iFAN: Inference-Aware Learning for Plain Mask Transformers

arXiv:2608.03216v1 Announce Type: new Abstract: Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inferenc

Improving Sample Efficiency in Multi-Agent Reinforcement Learning for Simulated Football Games via Exploration

arXiv:2503.13077v2 Announce Type: replace Abstract: Multi-agent reinforcement learning has shown promise in learning cooperative behaviors in team-based environments. However, such methods often deman

agentsarxiv-cs-lg

Internalising the Identity Primitive: Cryptographic Individuality for an Autonomous Agent on a Public Blockchain

arXiv:2608.02986v1 Announce Type: cross Abstract: A software agent on a public blockchain accumulates authority and economic stakes, raising the engineering question of what makes it count as an indiv

Internalizing Academic Writing Workflows for Introduction Generation via Struct-Aware Policy Learning

arXiv:2608.03138v1 Announce Type: cross Abstract: Generating a rigorous paper introduction with large language models (LLMs) remains challenging, since it requires coordinating background, gap identif

Interpreting Black-Box Large Language Models with Sentence-Level Energy Landscapes

arXiv:2608.02879v1 Announce Type: new Abstract: The widespread adoption of proprietary Large Language Models (LLMs) accessed strictly through closed APIs has created a critical challenge for responsib

local-aiarxiv-cs-ai

IPPRO: Importance-based Pruning with PRojective Offset for Magnitude-indifferent Structural Pruning

arXiv:2507.14171v3 Announce Type: replace-cross Abstract: Importance-based structured pruning overwhelmingly relies on filter magnitude. This proxy is fundamentally flawed: due to scale invariance, fu

JoyAI-Video-Edit: Real-Time Open-Ended Video Editing with Autoregressive Diffusion

arXiv:2608.03974v1 Announce Type: new Abstract: Real-time video editing requires low-latency causal generation with bounded computational resources while preserving source fidelity and long-term tempo

Keep the Needle, Prune the Haystack: Defect-Preserving Token Pruning for Efficient Zero-Shot Anomaly Detection

arXiv:2608.03681v1 Announce Type: new Abstract: Zero-shot visual anomaly detection has achieved remarkable progress, with recent vision-only approaches further improving performance while simplifying

local-aiarxiv-cs-cv

LatentGuard: Efficient and Inspectable Latent Reasoning for LLM Safeguards

arXiv:2608.03838v1 Announce Type: new Abstract: Reasoning-based guard models improve LLM safeguards, but decoding explicit rationales for every interaction makes them costly to deploy. Although latent

LeanMem: Simple and Efficient Long-Term Memory for LLM Agents

arXiv:2608.03463v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history. However, existing memory systems typic

Learning Context-Aware Motion Priors for Humanoid Control

arXiv:2608.03234v1 Announce Type: new Abstract: Motion priors provide powerful guidance for learning naturalistic humanoid behaviors. However, existing methods typically learn a general, task-agnostic

safetyarxiv-cs-ro

Learning Molecular Representations from Cellular Phenotypes with Structure Preservation

arXiv:2608.02688v1 Announce Type: cross Abstract: Phenotypic drug discovery enables the discovery of functional relationships between molecular structures and cellular responses. However, existing mul

Learning Music Style for Piano Arrangement Through Cross-Modal Bootstrapping

arXiv:2608.03050v1 Announce Type: cross Abstract: What is music style? Though often described using text labels such as 'swing,' 'classical,' or 'emotional,' the real style remains implicit and hidden

Lightweight 3D Object Detection via Mamba-Based Knowledge Distillation

arXiv:2608.03490v1 Announce Type: cross Abstract: 3D object detection using light detection and ranging (LiDAR) sensors requires a balance between accuracy and computational efficiency for onboard per

safetyarxiv-cs-cv

LiteMVS: Efficient Multi-View Stereo with Foundation Distillation and Expert Aggregation

arXiv:2608.03851v1 Announce Type: new Abstract: Real-time 3D perception is crucial for robotics, augmented reality, and embodied intelligence applications. Existing multi-view stereo (MVS) methods pri

Long-term Traffic Scene Prediction via Polynomial Representations in Autonomous Driving

arXiv:2608.03330v1 Announce Type: new Abstract: This thesis addresses fundamental challenges in traffic scene prediction for autonomous driving by introducing robust and computationally efficient mode

MAFIA: Query-Only Memory Attacks via Probing and Factual Injection against Audited LLM Agents

arXiv:2608.03844v1 Announce Type: new Abstract: Memory-augmented LLM agents rely on rich context for long-horizon reasoning and acting, yet their memory modules expose a persistent attack surface for

MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting

arXiv:2405.16440v2 Announce Type: replace-cross Abstract: In recent years, Transformers have become the de-facto architecture for long-term time series forecasting (LTSF), yet they face challenges ass

Mapping the City Through the Lens of Language Models

arXiv:2608.02971v1 Announce Type: new Abstract: Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and

researcharxiv-cs-cl

Applications

MaterialFusion: High-Quality, Zero-Shot, and Controllable Material Transfer with Diffusion Models

arXiv:2502.06606v3 Announce Type: replace Abstract: Manipulating the material appearance of objects in images is critical for applications like augmented reality, virtual prototyping, and digital cont

applicationsarxiv-cs-cv

Modeling Long-Term Memory and Temporal Attention Shifts for Video Salient Object Ranking with a New Benchmark

arXiv:2203.17257v2 Announce Type: replace Abstract: Salient Object Ranking (SOR) aims to estimate the relative saliency order among multiple salient objects. While SOR has been extensively studied in

Modeling Matches as Language: A Generative Transformer Approach for Counterfactual Player Valuation in Football

arXiv:2603.15212v2 Announce Type: replace Abstract: Evaluating football player transfers is challenging because player actions depend strongly on tactical systems, teammates, and match context. Despit

MoECa: Aligning Feature Reuse with Expert Decomposition in Diffusion Transformers

arXiv:2606.15615v2 Announce Type: replace-cross Abstract: Diffusion Transformers with Mixture-of-Experts (DiT-MoE) improve model capacity under sparse activation, but diffusion inference is still bott

MoEGen: Mixture-of-Experts for Instance-Adaptive LoRA Generation

model-releasesarxiv-cs-cl

arXiv:2608.03275v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) enables efficient adaptation of large language models, but existing MoE-based PEFT methods typically improve capa

Morphology-Aware Implicit Super-Resolution Network for Pathological Images

arXiv:2608.03664v1 Announce Type: new Abstract: Accurate diagnosis in Digital Pathology (DP) relies on high-resolution whole-slide images, yet clinical deployment is often limited by hardware costs. S