Search: “framework”

SD-ReID: View-aware Stable Diffusion for Aerial-Ground Person Re-Identification

arXiv:2504.09549v3 Announce Type: replace Abstract: Aerial-Ground Person Re-IDentification (AG-ReID) aims to retrieve specific persons across cameras with different viewpoints. Previous works focus on

researcharxiv-cs-cv

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Second-Order Actor-Critic Methods for Discounted MDPs via Policy Hessian Decomposition

DGX agent

arXiv:2605.14982v1 Announce Type: cross Abstract: We address the discounted reward setting in reinforcement learning (RL). To mitigate the value approximation challenges in policy gradient methods, ac

safetyarxiv-cs-ai

15 May 2026

SEDiT: Mask-Free Video Subtitle Erasure via One-step Diffusion Transformer

arXiv:2605.14894v1 Announce Type: new Abstract: Recent breakthroughs in video diffusion models have significantly accelerated the development of video editing techniques. However, existing methods oft

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

arXiv:2510.16196v2 Announce Type: replace-cross Abstract: Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to

applicationsarxiv-cs-ai

Semantic Feature Segmentation for Interpretable Predictive Maintenance in Complex Systems

arXiv:2605.14318v1 Announce Type: new Abstract: Predictive maintenance in complex systems is often complicated by the heterogeneity and redundancy of monitored variables,which can obscure fault-releva

SemaTune: Semantic-Aware Online OS Tuning with Large Language Models

arXiv:2605.15026v1 Announce Type: cross Abstract: Online OS tuning can improve long-running services, but existing controllers are poorly matched to live hosts. They treat scheduler, power, memory, an

Agents

Silent Collapse in Recursive Learning Systems

arXiv:2605.14588v1 Announce Type: new Abstract: Recursive learning -- where models are trained on data generated by previous versions of themselves -- is increasingly common in large language models,

agentsarxiv-cs-lg

Silent Neuron Theory and Plasticity Preservation for Deep Reinforcement Learning in Adaptive Video Streaming

arXiv:2505.01584v3 Announce Type: replace-cross Abstract: Adaptive video streaming optimizes Quality of Experience (QoE) metrics by selecting appropriate bitrates according to varying network bandwidt

applicationsarxiv-cs-ai

SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agents

arXiv:2605.14205v1 Announce Type: new Abstract: LLM-based web agents can navigate live storefronts, yet they often collapse to a single 'average buyer' policy, failing to capture the heterogeneous and

SkillFlow: Flow-Driven Recursive Skill Evolution for Agentic Orchestration

arXiv:2605.14089v1 Announce Type: new Abstract: In recent years, a variety of powerful LLM-based agentic systems have been applied to automate complex tasks through task orchestration. However, existi

Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations

arXiv:2605.14937v1 Announce Type: cross Abstract: Predictive world models enable agents to model scene dynamics and reason about the consequences of their actions. Inspired by human perception, object

Small, Private Language Models as Teammates for Educational Assessment Design

arXiv:2605.15015v1 Announce Type: new Abstract: Generative AI increasingly supports educational design tasks, e.g., through Large Language Models (LLMs), demonstrating the capability to design assessm

local-aiarxiv-cs-ai

SOCC-ICP: Semantics-Assisted Odometry based on Occupancy Grids and ICP

arXiv:2605.15074v1 Announce Type: new Abstract: Reliable pose estimation in previously unseen environments is a fundamental capability of autonomous systems. Existing LiDAR odometry methods typically

safetyarxiv-cs-ro

SpeakerLLM: A Speaker-Specialized Audio-LLM for Speaker Understanding and Verification Reasoning

arXiv:2605.15044v1 Announce Type: cross Abstract: As audio-first agents become increasingly common in physical AI, conversational robots, and screenless wearables, audio large language models (audio-L

SpectraFlow: Unifying Structural Pretraining and Frequency Adaptation for Medical Image Segmentation

arXiv:2605.14566v1 Announce Type: new Abstract: Medical image segmentation remains challenging in low-data regimes, where scarce annotations often yield poor generalization and ambiguous boundaries wi

Spectral Analysis of Fake News Propagation

arXiv:2605.13861v1 Announce Type: cross Abstract: The propagation structure of fake news has been shown to be an important cue for detecting it; yet, existing propagation-based fake news detection met

applicationsarxiv-cs-ai

SteerSeg: Attention Steering for Reasoning Video Segmentation

arXiv:2605.14908v1 Announce Type: new Abstract: Video reasoning segmentation requires localizing objects across video frames from natural language expressions, often involving spatial reasoning and im

Stochastic Matching via Local Sparsification

arXiv:2605.14195v1 Announce Type: cross Abstract: The classic online stochastic matching problem typically requires immediate and irrevocable matching decisions. However, in many modern decentralized

researcharxiv-cs-lg

SToRe3D: Sparse Token Relevance in ViTs for Efficient Multi-View 3D Object Detection

model-releasesarxiv-cs-cv

arXiv:2605.14110v1 Announce Type: new Abstract: Vision Transformers (ViTs) enable strong multi-view 3D detection but are limited by high inference latency from dense token and query processing across

StyleTextGen: Style-Conditioned Multilingual Scene Text Generation

model-releasesarxiv-cs-cv

arXiv:2605.14708v1 Announce Type: new Abstract: Style-conditioned scene text generation faces unique challenges in extracting precise text styles from complex backgrounds and maintaining fine-grained

Systematic Discovery of Semantic Attacks in Online Map Construction through Conditional Diffusion

arXiv:2605.14396v1 Announce Type: new Abstract: Autonomous vehicles depend on online HD map construction to perceive lane boundaries, dividers, and pedestrian crossings -- safety-critical road element

Teaching Large Language Models When Not to Know: Learning Temporal Critique for Ex-Ante Reasoning

arXiv:2605.14636v1 Announce Type: new Abstract: Large language models (LLMs) often fail to reason under temporal cutoffs: when prompted to answer from the standpoint of an earlier time, they exploit k

Temporal Fair Division in Multi-Agent Systems: From Precise Alternation Metrics to Scalable Coordination Proxies

arXiv:2605.14879v1 Announce Type: cross Abstract: A plethora real-world environments require agents to compete repeatedly for the same limited resource, calling for a temporal notion of fairness judge

safetyarxiv-cs-lg

TERMS-Bench: Diagnosing LLM Negotiation Agents Beyond Deal Rate

arXiv:2605.13909v1 Announce Type: cross Abstract: Negotiation is a central mechanism of economic exchange, shaping markets, procurement, labor agreements, and resource allocation. It is also a canonic

Text Knows What, Tables Know When: Clinical Timeline Reconstruction via Retrieval-Augmented Multimodal Alignment

arXiv:2605.15168v1 Announce Type: cross Abstract: Reconstructing precise clinical timelines is essential for modeling patient trajectories and forecasting risk in complex, heterogeneous conditions lik

The Evaluation Trap: Benchmark Design as Theoretical Commitment

arXiv:2605.14167v1 Announce Type: new Abstract: Every AI benchmark operationalizes theoretical assumptions about the capability it claims to assess. When assumptions function as unexamined commitments

Think When Needed: Adaptive Reasoning-Driven Multimodal Embeddings with a Dual-LoRA Architecture

model-releasesarxiv-cs-cl

arXiv:2605.14448v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have emerged as a powerful backbone for multimodal embeddings. Recent methods introduce chain-of-thought (CoT

TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA

arXiv:2510.04682v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely applied in real world scenarios, yet fine-tuning them comes with significant computational and storage

Tokenizing Single-Channel EEG with Time-Frequency Motif Learning

arXiv:2502.16060v5 Announce Type: replace-cross Abstract: Foundation models are reshaping EEG analysis, yet an important problem of EEG tokenization remains a challenge. This paper presents TFM-Tokeni

TOPOS: High-Fidelity and Efficient Industry-Grade 3D Head Generation

arXiv:2605.14594v1 Announce Type: new Abstract: High-fidelity 3D head generation plays a crucial role in the film, animation and video game industries. In industrial pipelines, studios typically enfor

applicationsarxiv-cs-cv

Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought

arXiv:2605.14866v1 Announce Type: cross Abstract: As modern microservice systems grow increasingly complex due to dynamic interactions and evolving runtime environments, they experience failures with

local-aiarxiv-cs-ai

Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning

arXiv:2605.14717v1 Announce Type: cross Abstract: Label-free single-cell imaging offers a scalable, non-invasive alternative to fluorescence-based cytometry, yet inferring molecular phenotypes directl

Towards Real-Time Autonomous Navigation: Transformer-Based Catheter Tip Tracking in Fluoroscopy

arXiv:2605.14253v1 Announce Type: new Abstract: Purpose: Mechanical thrombectomy (MT) improves stroke outcomes, but is limited by a lack of local treatment access. Widespread distribution of reinforce

Hardware

Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines

arXiv:2605.13981v1 Announce Type: cross Abstract: The rise in deployment of large language models has driven a surge in GPU demand and datacenter scaling, raising concerns about electricity use, grid

hardwarearxiv-cs-ai

Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning

arXiv:2605.13936v1 Announce Type: cross Abstract: The recent success of large language models (LLMs) has been largely driven by vast public datasets. However, the next frontier for LLM development lie

Training-Free Inference for High-Resolution Sinogram Completion

arXiv:2506.08809v5 Announce Type: replace Abstract: High-resolution sinogram completion is critical for computed tomography reconstruction, as missing projections can introduce severe artifacts. While

TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning

arXiv:2510.07118v3 Announce Type: replace Abstract: Instruction tuning is essential for aligning large language models (LLMs) to downstream tasks and commonly relies on large, diverse corpora. However

researcharxiv-cs-cl

Tutorials

TurboVGGT: Fast Visual Geometry Reconstruction with Adaptive Alternating Attention

arXiv:2605.14315v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction methods, such as visual geometry transformers, have substantially advanced the traditional per-scene optimization

tutorialsarxiv-cs-cv

UMo: Unified Sparse Motion Modeling for Real-Time Co-Speech Avatars

arXiv:2605.14731v1 Announce Type: cross Abstract: Speech-driven gestures and facial animations are fundamental to expressive digital avatars in games, virtual production, and interactive media. Howeve

Unbiased and Second-Order-Free Training for High-Dimensional PDEs

arXiv:2605.14643v1 Announce Type: new Abstract: Deep learning methods based on backward stochastic differential equations (BSDEs) have emerged as competitive alternatives to physics-informed neural ne

safetyarxiv-cs-lg

UniTriGen: Unified Triplet Generation of Aligned Visible-Infrared-Label for Few-Shot RGB-T Semantic Segmentation

arXiv:2605.14626v1 Announce Type: new Abstract: RGB-T semantic segmentation requires strictly aligned VIS-IR-Label triplets; however, such aligned triplet data are often scarce in real-world scenarios

Unlocking Complex Visual Generation via Closed-Loop Verified Reasoning

arXiv:2605.14876v1 Announce Type: cross Abstract: Despite rapid advancements, current text-to-image (T2I) models predominantly rely on a single-step generation paradigm, which struggles with complex s

Unsteady Metrics and Benchmarking Cultures of AI Model Builders

arXiv:2605.14164v1 Announce Type: new Abstract: The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases

Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling

arXiv:2605.13933v1 Announce Type: cross Abstract: Acquisition differences across sites, scanners, and protocols in dMRI introduce variability that complicates structural connectome analysis. This moti

Unsupervised simulation of incompressible flows with physics- and equality- constrained artificial neural networks

arXiv:2511.18820v2 Announce Type: replace-cross Abstract: Physics-informed neural networks (PINNs) have shown promise for solving partial differential equations, yet their success in simulating incomp

researcharxiv-cs-lg

Vendor-Conditioned Contrastive Learning for Predicting Organizational Cyber Threat Targets

model-releasesarxiv-cs-lg

arXiv:2012.14425v2 Announce Type: replace-cross Abstract: Cyberattacks cause billions of dollars in damage annually, with malicious hackers often sharing exploit code and techniques on underground for

Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation

arXiv:2602.02994v2 Announce Type: replace Abstract: Reinforcement learning has emerged as a principled post-training paradigm for Temporal Video Grounding (TVG) due to its on-policy optimization, yet

Video-Zero: Self-Evolution Video Understanding

arXiv:2605.14733v1 Announce Type: new Abstract: Self-evolution offers a promising path for improving reasoning models without relying on intensive human annotation. However, extending this paradigm to

researcharxiv-cs-cv