Search: “framework”

Interpretable ODE-style Generative Diffusion Model via Force Field Construction

arXiv:2303.08063v4 Announce Type: replace Abstract: For a considerable time, researchers have focused on developing a method that establishes a deep connection between the generative diffusion model a

applicationsarxiv-cs-cv

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Intervention-Aware Clinical World Model for Post-Op Outcome Forecasting in Cardiology

DGX agent

arXiv:2608.13518v1 Announce Type: cross Abstract: Many clinical prediction models treat post-intervention outcomes as a one-step mapping from baseline measurements to a future endpoint. However, recov

researcharxiv-cs-cv

14 Aug 2026

JailWAM: Jailbreaking World Action Models in Robot Control

arXiv:2604.05498v2 Announce Type: replace Abstract: World Action Models (WAMs) have emerged as a promising paradigm for robotic manipulation, enabling physical interaction across diverse tasks and env

safetyarxiv-cs-ro

Labels Are Not Endpoints: Treatment Leakage and Construct Validity in MCP Agent Security Evaluation

arXiv:2608.12880v1 Announce Type: cross Abstract: Security evaluations of tool-using agents often equate stored labels with behavioral facts. We audit a preserved campaign by tracing 10,200 execution

agentsarxiv-cs-ai

Learning Latency-Aware Orchestration for Multi-Agent Systems

arXiv:2601.10560v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) coordinate multiple LLM-powered agents through structured workflows, gaining reasoning power but incurring high infe

agentsarxiv-cs-ai

Learning Under Treatment-Induced Label Indeterminacy with Expert Annotations of Counterfactual Outcomes: A Case Study in Neurological Prognostication

arXiv:2608.12477v1 Announce Type: new Abstract: Clinical prediction models are often developed as if the outcome of interest were cleanly observed for every patient. This assumption fails when treatme

safetyarxiv-cs-lg

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods

arXiv:2608.13333v1 Announce Type: new Abstract: Large neighborhood search normally selects a random subset of decision variables for iterative optimization. For efficiently solving different problems,

local-aiarxiv-cs-ai

LLMs Are Not Good Strategists, Yet Memory-Enhanced Agency Boosts Reasoning

arXiv:2608.12626v1 Announce Type: cross Abstract: Strategic reasoning in Large Language Models (LLMs) within long-horizon environments is often limited by inconsistent subgoals. In these settings, fin

local-aiarxiv-cs-ai

LOB-ID: Evaluating Synthetic Market Data by Inception Distances

arXiv:2608.13082v1 Announce Type: cross Abstract: Generative models of limit orderbook (LOB) data have advanced rapidly, but their evaluation often focuses on stylised facts and selected market statis

Localize, Then Reason: Visual Latent Structural Reasoning for Molecular Properties and Edits

arXiv:2608.13244v1 Announce Type: new Abstract: Local chemical perception and property reasoning are both essential for understanding how molecular structure determines properties. Current LLM-based c

local-aiarxiv-cs-cl

LoRA-Diffusion: Parameter-Efficient Fine-Tuning via Low-Rank Trajectory Decomposition

model-releasesarxiv-cs-cl

arXiv:2608.12328v1 Announce Type: new Abstract: Parameter-efficient fine-tuning methods such as LoRA have transformed the adaptation of large autoregressive language models, enabling task-specific cus

LycheeMemory V2: Efficient Long-Term Memory for LLM Agents via Semantic Segment-Level Consolidation

model-releasesarxiv-cs-cl

arXiv:2608.12990v1 Announce Type: new Abstract: Long-horizon LLM agents must preserve information from past interactions to support future tasks. Existing memory systems typically rely on eager consol

MAG: MAnifold Guided Semi-Supervised Multi-modal In-Context Learning

model-releasesarxiv-cs-lg

arXiv:2608.12724v1 Announce Type: new Abstract: Few-shot in-context learning (ICL) with multi-modal large language models (MLLMs) enables task adaptation without parameter updates, but its performance

Mind the Context: Continual Learning of Socially Appropriate Robot Actions via Environmental-Social Disentanglement

arXiv:2608.13448v1 Announce Type: new Abstract: Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., st

agentsarxiv-cs-ro

Mixture of Training: Recombining Small-Scale Scaffolded Pretraining Runs into a Larger Language Model

arXiv:2608.13277v1 Announce Type: cross Abstract: We ask whether language-model pre-training can be decomposed into smaller, independently trainable jobs that can later be recomposed into a coherent l

NaviDC-OCR: Navigating Document Parsing Across Digital and Camera-Captured Documents

arXiv:2608.12898v1 Announce Type: cross Abstract: Document parsing aims to transform unstructured documents into structured and machine-readable representations. Recent advances in Vision-Language Mod

NestDex: Nested Policy Learning with Copilot Assisted Teleoperation for Dexterous Manipulation

arXiv:2608.13362v1 Announce Type: new Abstract: Dexterous manipulation promises substantially richer robot interaction with the physical world, but learning these behaviours remains constrained by the

safetyarxiv-cs-ro

Tutorials

New Terms, New Toxicity: Consensus-based Chinese Neologism Toxicity Detection via Search-Augmented LLMs

arXiv:2608.12361v1 Announce Type: new Abstract: Neologisms, emerging terms in meaning or form, can serve as new vehicles for toxic expression, like 'country girl' as a stigmatizing label targeting fem

tutorialsarxiv-cs-cl

OGR-MARL: Option-Guided Residual Multi-Agent Reinforcement Learning for Heterogeneous USV Cooperative Pursuit in Constrained Port Waterways

arXiv:2608.12995v1 Announce Type: new Abstract: Heterogeneous USV cooperative pursuit in constrained port waterways requires evader interception under navigation, traffic, and role constraints. This p

safetyarxiv-cs-ai

On Measuring Semantic Preservation in Legal Ontology Learning

arXiv:2608.12326v1 Announce Type: new Abstract: Ontology learning transforms unstructured text into structured representations for automated reasoning. Yet structuring information risks losing it, and

applicationsarxiv-cs-cl

On the Structural Limits of Machine Learning Decision Systems: An Information-Theoretic, Interaction-Based, and Stochastic-Dynamical Perspective

arXiv:2608.13510v1 Announce Type: cross Abstract: Machine learning procedures are commonly evaluated in terms of predictive accuracy and computational efficiency. However, their achievable performance

agentsarxiv-cs-lg

Perception-Aware Autonomous Exploration in Feature-Limited Environments

arXiv:2603.15605v2 Announce Type: replace Abstract: Autonomous exploration in unknown environments typically relies on onboard state estimation for localisation and mapping. Existing exploration metho

agentsarxiv-cs-ro

Perturbation-based Regional Interpretability through Subtraction Mapping (PRISM): naming-error dissociations in language models and post-stroke aphasia

arXiv:2608.12717v1 Announce Type: cross Abstract: Mechanistic interpretability of large language models lacks spatially resolved, falsifiable tools for testing whether internal components are speciali

researcharxiv-cs-cl

PIPES: Securing Agent Perception with Provenance and Priors

arXiv:2608.12789v1 Announce Type: cross Abstract: Tool-using agents consume external data from sources with different levels of trust, yet tool responses rarely identify who produced each component or

Practice Makes Unsafe: Skill Misevolution in Self-Improving LLM Agents

arXiv:2608.12851v1 Announce Type: new Abstract: Self-improving LLM agents convert successful trajectories into persistent cross-task state. An unsafe success can thereby become reusable policy after i

safetyarxiv-cs-ai

PROVE-RT: Generating Mechanized Theorem Prover Scripts for Real-Time Systems using LLMs

arXiv:2608.12762v1 Announce Type: new Abstract: Schedulability analysis is essential for certifying real-time systems, but existing tests are often developed through pen-and-paper proofs that are diff

QUIETT: Query-Independent Table Transformation for Robust Reasoning

arXiv:2602.20017v2 Announce Type: replace Abstract: Real-world tables often contain schema inconsistencies, heterogeneous value formats, and implicit relational structures that degrade table reasoning

agentsarxiv-cs-cl

Tutorials

RadarGen: Automotive Radar Point Cloud Generation from Cameras

arXiv:2512.17897v2 Announce Type: replace-cross Abstract: We present RadarGen, a diffusion model for synthesizing realistic automotive radar point clouds from multi-view camera imagery. RadarGen adapt

tutorialsarxiv-cs-ai

RAGSieve: Self-Referenced Local Contrast for Knowledge-Poison Detection in Retrieval-Augmented Generation

arXiv:2608.13010v1 Announce Type: new Abstract: Retrieval-augmented generation treats an external corpus as inference evidence, allowing injected documents to promote attacker-chosen claims. Existing

researcharxiv-cs-cl

RbFT-Net: Rectify-Before-Fuse Temporal Radar Anchors for 4D Radar-Camera Depth Completion

arXiv:2608.13102v1 Announce Type: new Abstract: Dense metric depth prediction from cameras and millimeter-wave radar offers a cost-effective sensing solution for autonomous systems. However, radar mea

agentsarxiv-cs-cv

Represent, Then Generate: Multimodal-Conditioned Time-Series Generation under Irregular Missingness

arXiv:2608.12592v1 Announce Type: new Abstract: Continuous physiological time series underpin modern clinical monitoring, yet many of the most informative signals are invasive, expensive, or simply un

researcharxiv-cs-lg

RGB-D Video Generation for Improving Human-to-Robot Object Handover Prediction

arXiv:2608.13028v1 Announce Type: new Abstract: Human-to-robot (H2R) object handover is a fundamental capability for human-robot collaboration, yet progress is hindered by the scarcity of large-scale,

applicationsarxiv-cs-cv

RulerNet: Learning Perspective-Invariant Ruler Representations for Robust Image Scale Estimation

arXiv:2507.07077v2 Announce Type: replace Abstract: Accurately converting pixel measurements into absolute real-world dimensions remains a fundamental challenge in computer vision, limiting progress i

local-aiarxiv-cs-cv

SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization

arXiv:2608.13538v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are proposed to extract numerous features from large language model (LLM) representations, yet explaining these features stil

researcharxiv-cs-cl

SAP-Nav: Spatial Semantic Representation Meets Active Perception for Hierarchical Open-Vocabulary Object Navigation

arXiv:2608.12707v1 Announce Type: new Abstract: Hierarchical open-vocabulary object navigation (OVON) requires agents to follow free-form instructions that may specify targets through scene-, room-, r

agentsarxiv-cs-ro

SCOPE: Subspace Clustering with Online Per-Head Top-K Estimation for Sparse Video Attention

arXiv:2608.12780v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) incur quadratic self-attention cost over spatiotemporal tokens. Existing training-free sparse attention methods often cons

researcharxiv-cs-cv

SCULPT: Subtractive Composition for 3D Part Generation

model-releasesarxiv-cs-cv

arXiv:2608.13541v1 Announce Type: new Abstract: Part-aware 3D generation aims to create digital assets that are coherent as complete objects while exposing structural parts for editing, material assig

SelfDRSC++: Self-Supervised Dual Reversed Rolling Shutter Correction via Video Interpolation

arXiv:2408.11411v2 Announce Type: replace Abstract: Modern consumer cameras often use rolling shutter, capturing scenes row-by-row and causing distortion in dynamic scenes. Existing correction methods

applicationsarxiv-cs-cv

SEMA: Simple yet Effective Learning for Multi-Turn Jailbreak Attacks

arXiv:2602.06854v2 Announce Type: replace Abstract: Multi-turn jailbreaks capture the real threat model for safety-aligned chatbots, where single-turn attacks are merely a special case. Yet existing a

safetyarxiv-cs-cl

SketchSense: Learning to Interpret Imperfect Sketch Guidance for Image Inpainting

arXiv:2608.13186v1 Announce Type: new Abstract: Sketch-guided image inpainting provides intuitive structural control, yet real sketches often mix reliable global intent with locally crowded, displaced

local-aiarxiv-cs-cv

Spa3R: Predictive Spatial Field Modeling for 3D Visual Reasoning

arXiv:2602.21186v2 Announce Type: replace Abstract: Vision-language models excel at 2D visual understanding but remain limited in 3D spatial reasoning. Existing approaches either depend on explicit 3D

researcharxiv-cs-cv

SPADE: Speculative Decoding for Precise and Low Cost Distributed Edge Cloud Inference

arXiv:2608.13076v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable success in natural language understanding and generation, but their deployment is constrained by h

applicationsarxiv-cs-ai

SPARED: Reasoning-Based AI-Generated Image Detection via Adversarially Edited Data

arXiv:2608.12876v1 Announce Type: cross Abstract: Detecting AI-generated images is only half the task: a deployed detector must also justify its verdict, yet existing detectors inherit three failure m

Spatial Memory Agent: Experience-Grounded Procedure Memory for Spatial Intelligence

arXiv:2608.12743v1 Announce Type: new Abstract: Spatial intelligence is becoming a foundation for embodied agents, robotic planning, and multimodal assistants. To improve the spatial reasoning ability

SpinCastML an Open Decision-Making Application for Inverse Design of Electrospinning Manufacturing: A Machine Learning, Optimal Sampling and Inverse Monte Carlo Approach

model-releasesarxiv-cs-lg

arXiv:2602.09120v2 Announce Type: replace Abstract: Electrospinning is a powerful technique for producing micro to nanoscale fibers with application specific architectures. Small variations in solutio

Steering the Language Axis: From Linear Decodability to Causal Control

arXiv:2608.12334v1 Announce Type: cross Abstract: Despite the impressive multilingual capabilities of Large Language Models, the latent dynamics dictating language selection remain poorly understood.

StorySpark: Module-wise Evolutionary Search for Story Premise Generation

arXiv:2608.12336v1 Announce Type: cross Abstract: A story premise is the creative spark from which a full narrative can grow. Yet LLM-based story generation has mostly emphasized later-stage planning,

Structured Local Differential Modeling for AI-Generated Image Detection

arXiv:2608.12811v1 Announce Type: new Abstract: The rapid advancement of AI-generated content has made the reliable detection of generated images an increasingly critical challenge. Existing detection

local-aiarxiv-cs-cv