Search: “framework”

Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development

arXiv:2608.13417v1 Announce Type: new Abstract: Autonomous agents are increasingly capable of improving models, systems, and other technical artifacts through long-horizon experimentation. To understa

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

Beyond Simulated Benchmarks: Evaluating Motion Representations for Fall Detection Under Real-World Data Scarcity

DGX agent

arXiv:2608.13197v1 Announce Type: new Abstract: Falls are a major health concern for older adults, and wearable sensors have been widely explored for detecting falls and enabling timely intervention.

applicationsarxiv-cs-lg

14 Aug 2026

Beyond Visual Evidence: Revealing and Mitigating Relational Privacy Leakage in Document MLLMs

arXiv:2608.12911v1 Announce Type: new Abstract: While the privacy risks of multimodal large language models (MLLMs) have drawn significant attention, the unique vulnerabilities of domain-specific MLLM

Black-Box Knowledge Transfer across Distinct Feature Sets

arXiv:2608.12403v1 Announce Type: cross Abstract: Pre-trained black-box predictive functions encode knowledge distilled from massive datasets and extensive computation. However, when the available inp

BoardroomAI: Dependency-Aware Human-Steerable Multi-Agent Deliberation through Evolving Decision Graphs

arXiv:2608.13046v1 Announce Type: new Abstract: Organizational decisions are co-created while evidence, constraints, and human priorities continue to evolve. In conventional transcript-based multi-age

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

arXiv:2608.12854v1 Announce Type: cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typical

Chance-constrained selection of sequential intervention strategies from counterfactual estimates

arXiv:2608.13209v1 Announce Type: cross Abstract: Many operational decisions are sequences of interventions under a cumulative resource limit, such as a maintenance schedule within a crew-hour budget.

safetyarxiv-cs-lg

CityRiSE: Reasoning Urban Socio-Economic Status in Large Vision-Language Models via Reinforcement Learning

arXiv:2510.22282v2 Announce Type: replace-cross Abstract: Urban socio-economic sensing plays a vital role in advancing global sustainable development goals. With the advent of Large Vision-Language Mo

researcharxiv-cs-ai

Tutorials

Class Geometry as Supervision for Sample-Efficient Open-World Detection

arXiv:2608.12698v1 Announce Type: new Abstract: Open-world object detection requires models to recognize known categories, reject unfamiliar objects, and incorporate new classes over time. This is esp

tutorialsarxiv-cs-cv

CoMedBench: A Multi-Source Benchmark of Synthetic Medical Data Fidelity and Downstream Utility

model-releasesarxiv-cs-lg

arXiv:2608.12805v1 Announce Type: new Abstract: Access to clinical data is essential for developing reliable healthcare machine learning systems, but direct use of electronic health records is constra

Comparative Analysis of Multilingual Pre-trained Models for Nepali Automatic Speech Recognition

arXiv:2608.12327v1 Announce Type: cross Abstract: Multilingual pretrained models nominally support Nepali, yet no controlled benchmark has compared them under a single fine-tuning protocol. We fine-tu

Confidence-Calibrating Regularization for Robust Brain MRI Segmentation Under Domain Shift

arXiv:2509.23176v2 Announce Type: replace Abstract: The Segment Anything Model (SAM) exhibits strong zero-shot performance on natural images but suffers from domain shift and overconfidence when appli

researcharxiv-cs-cv

Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation

arXiv:2608.13391v1 Announce Type: new Abstract: Interactive autoregressive video generation demands both low-latency rollouts and precise online control. Few-step distillation accelerates generation b

safetyarxiv-cs-cv

CoverPrune: Coverage-Driven Token Pruning for 3D VLMs via Optimal Transport

arXiv:2608.13226v1 Announce Type: cross Abstract: While 3D Vision-Language Models (3D VLMs) have demonstrated remarkable spatial reasoning capabilities, they suffer from massive visual token counts th

researcharxiv-cs-ai

DAPD: Dual-Anchored Policy Distillation

arXiv:2608.01735v2 Announce Type: replace Abstract: On-policy (self) distillation (OPSD) is increasingly adopted for language-model post-training. It strengthens the teacher with privileged informatio

safetyarxiv-cs-ai

DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation

arXiv:2608.12980v1 Announce Type: new Abstract: Referring remote sensing image segmentation (RRSIS) aims to delineate targets specified by natural language expressions in remote sensing imagery. Exist

local-aiarxiv-cs-cv

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming

arXiv:2608.12757v1 Announce Type: cross Abstract: Laplacian-regularized minimization is fundamental in signal processing and machine learning, but is limited by the dense and ill-conditioned nature of

Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference

arXiv:2608.12921v1 Announce Type: cross Abstract: The performance of large language model (LLM)-based multi-agent systems (MAS) largely depends on effective communication topologies. Existing topology

Distribution Steering via Sliced Optimal Transport Control

arXiv:2608.12828v1 Announce Type: cross Abstract: Distribution steering seeks feedback laws that drive the state law of a dynamical system between prescribed initial and terminal distributions. Optima

Edit2TikZ: A Comprehensive and Challenging Benchmark for Scientific Figure Editing with TikZ

arXiv:2608.13441v1 Announce Type: new Abstract: Although multimodal large language models (MLLMs) have shown substantial potential in visual understanding and graphic code generation, editing scientif

Efficient Image Restoration with State-Dependent Forward Diffusion

arXiv:2505.16733v3 Announce Type: replace Abstract: This paper proposes to perform image restoration through a state-dependent mean-reverting forward diffusion (FoD) process. In contrast to traditiona

EgoCITE: Context-Augmented Indexing and Time-Aware Retrieval for Long-Horizon Egocentric Memory

arXiv:2608.12627v1 Announce Type: cross Abstract: Long-horizon egocentric memory transforms continuous first-person video and audio into a searchable record of past experiences. We demonstrate two bot

local-aiarxiv-cs-ai

EgoMonth: A Month-Level Egocentric Video Benchmark for Long-Term Spatiotemporal Memory

arXiv:2608.13113v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have led to substantial progress in video understanding, accompanied by a growing number o

Hardware

Enhancing Virtual Agents through SLMs and Edge-Computing: An Exploratory Evaluation of Think and Memory Processes

arXiv:2608.13420v1 Announce Type: new Abstract: Embodied intelligent virtual agents are expected to operate as persistent, adaptive, and context-aware entities within complex virtual and Metaverse wor

hardwarearxiv-cs-ai

Entropy-Augmented Multi-Objective Policy Optimization in Multiagent Systems

arXiv:2608.12534v1 Announce Type: cross Abstract: Autonomous agent teams deployed in settings such as marine and extraterrestrial outposts must coordinate actions to achieve optimal outcomes across mu

safetyarxiv-cs-ro

ERSkill: Evolving for Skill-Guided Adaptive Memory Retrieval

arXiv:2608.12720v1 Announce Type: cross Abstract: While Large Language Model (LLM) agents increasingly rely on long-term memory for persistent interactions, the retrieval mechanisms governing this mem

Tutorials

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces

arXiv:2608.13455v1 Announce Type: new Abstract: Medical foundation models learn latent representations of clinically meaningful phenotypes, yet their ability to support controllable image generation r

tutorialsarxiv-cs-cv

EvoTale: Continual Character Customization for Expanding Story Worlds

arXiv:2603.16285v2 Announce Type: replace Abstract: Character-centric story visualization aims to synthesize coherent image sequences that depict narrative events and interactions while preserving rec

safetyarxiv-cs-cv

Exploring Instruction Data Quality for Explainable Image Quality Assessment

arXiv:2510.03880v2 Announce Type: replace Abstract: In recent years, with the rapid development of large multimodal models (LMMs), explainable image quality assessment (IQA) has attracted increasing a

researcharxiv-cs-cv

Exploring Sparsity for Parameter Efficient Fine Tuning Using Wavelets for Vision

arXiv:2505.12532v3 Announce Type: replace-cross Abstract: Efficiently adapting large pretrained models is critical under tight compute and memory budgets. While Parameter-Efficient Fine-Tuning (PEFT)

Tutorials

Exponential quantum advantage for learning signals with a single qubit

arXiv:2608.13521v1 Announce Type: cross Abstract: Quantum technology has the potential to transform scientific discovery, but quantum advantages often require processing capabilities well beyond the r

tutorialsarxiv-cs-lg

Fine-tuned Normalizing Flows for ALICE Zero Degree Calorimeter Fast Simulation

arXiv:2608.12795v1 Announce Type: cross Abstract: Simulating the ALICE Zero Degree Calorimeter (ZDC) neutron detector responses at the LHC is computationally expensive, requiring complex Monte Carlo c

FIRE-VLA: Failure-Informed Self-Evolution for Vision-Language-Action Models in Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2608.13395v1 Announce Type: new Abstract: Reinforcement learning improves autonomous-driving vision-language-action (VLA) models by evaluating trajectories sampled from the current policy. Group

FlashDrive: Flash Vision-Language-Action Inference for Autonomous Driving

arXiv:2608.12932v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise to bring end-to-end reasoning to autonomous driving, but their computational cost remains far too high for r

From Local Mismatch to Global Impact: Optimizing Cache Reuse Policy for Efficient Diffusion

arXiv:2608.13043v1 Announce Type: new Abstract: Diffusion models have achieved dominant performance in visual generation but suffer from substantial inference overhead. While cache-based acceleration

local-aiarxiv-cs-ai

FSGR: Mitigating Token Frequency Bias for Fair SID-Based Generative Recommendation

arXiv:2608.12845v1 Announce Type: cross Abstract: Semantic ID (SID)-based generative recommendation has recently achieved remarkable success. However, existing methods suffer from a previously overloo

safetyarxiv-cs-ai

FUSE: Active Functional Affordance Grounding through Adaptive Semantic-Geometric Evidence Acquisition

arXiv:2608.12683v1 Announce Type: cross Abstract: Embodied agents must often identify and interact with objects based on their function rather than their identity, requiring them to actively acquire o

Generative Universal Multimodal Retrieval with Dual-role Identifiers

arXiv:2608.12987v1 Announce Type: cross Abstract: Generative information retrieval (GIR) has emerged as a compelling alternative to the conventional index-retrieve-then-rank retrieval pipeline by trai

GS^{2}CI: Robust Gaussian Splatting For Snapshot Compressive Imaging via Large Vision Model Priors

arXiv:2608.13502v1 Announce Type: new Abstract: Snapshot Compressive Imaging (SCI) offers an efficient solution for high-speed video acquisition and, under exposure-time camera--scene relative motion,

researcharxiv-cs-cv

Applications

H-VAEP and H-xT: Valuing Offensive On-the-Ball Actions in Handball by Estimating Probabilities

arXiv:2608.12926v1 Announce Type: cross Abstract: Traditional player evaluation in professional handball relies on basic box-score metrics or heuristic indices, which fail to credit the multi-player b

applicationsarxiv-cs-ai

H2R-Bench: Benchmarking Human-to-Robot Manipulation Video Generation in World Models

arXiv:2608.13049v1 Announce Type: cross Abstract: Large-scale manipulation data is essential for robot learning, yet collecting robot demonstrations remains expensive and difficult to scale. Meanwhile

HC-RAG: Evidence-Centric Retrieval-Augmented Generation over Heterogeneous Financial Filings

model-releasesarxiv-cs-cl

arXiv:2608.12335v1 Announce Type: new Abstract: Financial question answering over annual reports requires more than retrieving semantically similar passages. It often involves identifying relevant com

Heterogeneous Vision-Language Ensemble with Disagreement-Aware Reranking for Text-Based Person Anomaly Retrieval

arXiv:2608.12843v1 Announce Type: cross Abstract: Text-based person anomaly retrieval aims to retrieve pedestrians exhibiting anomalous behaviors from a large image gallery using natural language desc

HiRoute: Hierarchical Routed Prompt Tuning for Safety Alignment of Large Language Models

model-releasesarxiv-cs-lg

arXiv:2608.12821v1 Announce Type: new Abstract: Large language models (LLMs) remain vulnerable to harmful requests and jailbreak attacks. Parameter-efficient safety alignment methods based on prompt t

How Do VLMs Behave When Blind or Misled? Behavioral Evaluation of VLMs on Scientific Figures

arXiv:2608.13267v1 Announce Type: cross Abstract: Existing vision-language model (VLM) benchmarks emphasize perception and reasoning accuracy (how well VLMs describe and reason about what they see in

HPSD: Hybrid-Policy Self-Distillation for Text-Image-to-Video Diffusion Models

arXiv:2608.13205v1 Announce Type: new Abstract: Text-Image-to-Video (TI2V) models are an emerging unified architecture, where a single model simultaneously supports text-to-video (T2V) and image-to-vi

local-aiarxiv-cs-cv

HybridSB-MoE: Dual-Domain Schrodinger Bridges with Scene-Adaptive Expert Routing for Speech Enhancement

arXiv:2608.12715v1 Announce Type: cross Abstract: Generative speech enhancement faces three gaps: spectral models capture harmonic structure but often disrupt phase, waveform models preserve phase but

safetyarxiv-cs-ai

In Silico Study for Optimizing Intensity and Focality Electrode Configurations for Directional DBS Under Uncertainty Using Metaheuristic L1L1 Method

arXiv:2506.13452v3 Announce Type: replace-cross Abstract: Background and Objective: As Deep Brain Stimulation (DBS) advances toward directional leads and optimization-based current steering, selecting

safetyarxiv-cs-lg