Search: “model-releases”

SADGE: Structure and Appearance Domain Gap Estimation of Synthetic and Real Data

arXiv:2605.22467v1 Announce Type: new Abstract: We propose SADGE, a quantitative similarity metric that predicts the performance of synthetic image datasets for common computer vision tasks without do

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SceneGraphGrounder: Zero-Shot 3D Visual Grounding via Structured Scene Graph Matching

DGX agent

arXiv:2605.21788v1 Announce Type: new Abstract: Zero-shot 3D visual grounding requires localizing objects in unstructured environments from free-form natural language. Recent vision-language model (VL

model-releasesarxiv-cs-cv

22 May 2026

SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals

arXiv:2605.21919v1 Announce Type: new Abstract: Assessing progress toward the Sustainable Development Goals (SDGs) requires multi-step reasoning over visual cues, contextual knowledge, and development

Security Document Classification with a Fine-Tuned Local Large Language Model: Benchmark Data and an Open-Source System

arXiv:2605.20368v1 Announce Type: cross Abstract: Organizations that scan documents for sensitive information face a practical problem. Cloud services require data to be sent to external infrastructur

Seeing the Poem: Image-Semantic Detection of AI-Generated Modern Chinese Poetry with MLLMs

arXiv:2605.22654v1 Announce Type: new Abstract: Previous detection studies have shown that LLMs cannot be effectively used as detectors, but these studies have not addressed modern Chinese poetry. Mor

SegGuidedNet: Sub-Region-Aware Attention Supervision for Interpretable Brain Tumor Segmentation

arXiv:2605.22572v1 Announce Type: new Abstract: Accurate segmentation of brain tumour sub-regions from multi-parametric MRI is critical for treatment planning yet remains challenging due to morphologi

Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding

arXiv:2605.21852v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret invo

SFN-YOLO: Towards Free-Range Poultry Detection via Scale-aware Fusion Networks

arXiv:2509.17086v2 Announce Type: replace Abstract: Detecting and localizing poultry is essential for advancing smart poultry farming. Despite the progress of detection-centric methods, challenges per

SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm

arXiv:2602.08064v2 Announce Type: replace-cross Abstract: The long-standing tension between Pre- and Post-Norm remains an open problem in Transformer architecture, reflecting a fundamental trade-off b

SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control

arXiv:2511.07820v3 Announce Type: replace-cross Abstract: Despite the rise of billion-parameter foundation models trained across thousands of GPUs, similar scaling gains have not been shown for humano

SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation

arXiv:2605.22536v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have made rapid progress in spatial intelligence, yet existing spatial reasoning benchmarks largely assume pr

SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

arXiv:2512.10719v2 Announce Type: replace Abstract: End-to-end autonomous driving methods built on vision language models (VLMs) have undergone rapid development driven by their universal visual under

Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action

model-releasesarxiv-cs-ro

arXiv:2605.22283v1 Announce Type: new Abstract: We introduce SOMA, the Spatial Memory framework for Out-of-Vision Manipulation in Vision-Language-Action (VLA) models. Most existing VLAs implicitly ass

Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning

model-releasesarxiv-cs-ro

arXiv:2605.22456v1 Announce Type: new Abstract: Cloud-hosted LLM driver agents provide useful semantic judgments, but their inference latency exceeds stepwise vehicle-control windows. Learned world mo

Structural Anchor Pruning: Training-Free Multi-Vector Compression for Visual Document Retrieval

arXiv:2601.20107v2 Announce Type: replace-cross Abstract: Recent Vision-Language Models (e.g., ColPali) enable fine-grained Visual Document Retrieval (VDR) but incur prohibitive multi-vector index sto

Structure Retention in Embedding Spaces as a Predictor of Benchmark Performance

arXiv:2605.22202v1 Announce Type: new Abstract: In this paper, we show that high-performing embedding models organize their embedding spaces in a consistent way. We evaluate 25 contemporary embedding

Sub-exponential Growth Dynamics in Complex Systems: A Piecewise Power-Law Model for the Diffusion of New Words and Names

arXiv:2511.04106v5 Announce Type: replace-cross Abstract: The diffusion of ideas and language in society has conventionally been described by S-shaped models, such as the logistic curve. However, the

SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure

arXiv:2605.21198v1 Announce Type: cross Abstract: Public events on social media generate large volumes of discussion whose collective dynamics carry direct value for opinion forecasting and crisis res

Survive or Collapse: The Asymmetric Roles of Data Gating and Reward Grounding in Self-Play RL

arXiv:2605.22217v1 Announce Type: cross Abstract: Self-play reinforcement learning trains language models on their own generated tasks, co-evolving a proposer and solver without human labels. Recent s

Tackle CSM in JPEG Steganalysis with Data Adaptation

arXiv:2605.21523v1 Announce Type: cross Abstract: Steganalysis models excel on benchmark datasets but struggle in the wild when analyzed images are produced by a processing pipeline unseen during trai

Targeting Clause Type Distributions: a Picklock for Random Satisfiability Problems

arXiv:2605.20328v1 Announce Type: cross Abstract: Optimization problems such as the NP-complete 3-SAT provide an important benchmark for the difficult task of finding ground-states in strongly correla

Teaching AI Through Benchmark Construction: QuestBench as a Course-Based Practice for Accountable Knowledge Work

arXiv:2605.21413v2 Announce Type: new Abstract: As AI becomes part of everyday learning, many courses teach students to use it mainly as a productivity tool: how to prompt, search, summarize, write, c

Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation

arXiv:2605.21491v1 Announce Type: cross Abstract: As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and fil

Temporal Coding as a Substrate for Sensorimotor Object Inference: A Spiking Reinterpretation of Thousand Brains Architecture

model-releasesarxiv-cs-ro

arXiv:2605.22206v1 Announce Type: cross Abstract: The Thousand Brains Theory (TBT) and its open-source Monty framework model object recognition through sensorimotor inference -- identifying objects by

Thermo-VL: Extending Vision-Language Models to Thermal Infrared Perception

arXiv:2605.21882v1 Announce Type: new Abstract: Vision-language models (VLMs) often fail under low illumination because their visual grounding is learned predominantly from RGB imagery, whereas therma

Token-Level LLM Collaboration via FusionRoute

arXiv:2601.05106v4 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strengths across diverse domains. However, achieving strong performance across these domains with a singl

Tokenization with Split Trees

arXiv:2605.22705v1 Announce Type: new Abstract: We introduce Tokenization with Split Trees (ToaST), a subword tokenization method that directly optimizes compression under a new recursive inference pr

Towards Clinically Interpretable Ophthalmic VQA via Spatially-Grounded Lesion Evidence

arXiv:2605.22414v1 Announce Type: new Abstract: Visual Question Answering (VQA) holds great promise for clinical support, particularly in ophthalmology, where retinal fundus photography is essential f

Towards Selection of Large Multimodal Models as Engines for Burned-in Protected Health Information Detection in Medical Images

arXiv:2511.02014v2 Announce Type: replace Abstract: The detection of Protected Health Information (PHI) in medical imaging is critical for safeguarding patient privacy and ensuring compliance with reg

Training-Trajectory-Aware Token Selection

arXiv:2601.10348v2 Announce Type: replace Abstract: Efficient distillation is a key pathway for converting expensive reasoning capability into deployable efficiency, yet in the frontier regime where t

Transcription and Recognition of Italian Parliamentary Speeches Using Vision-Language Models

arXiv:2603.28103v2 Announce Type: replace-cross Abstract: Parliamentary proceedings represent a rich yet challenging resource for computational analysis, particularly when preserved only as scanned hi

TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route Generation

arXiv:2605.22355v1 Announce Type: new Abstract: Public transit route planning traditionally depends on structured map infrastructure and complex routing engines, and no existing dataset supports train

Transporting Task Vectors across Different Architectures without Training

arXiv:2602.12952v2 Announce Type: replace-cross Abstract: Adapting large pre-trained models to downstream tasks often produces task-specific parameter updates that are expensive to relearn for every m

Two is better than one: A Collapse-free Multi-Reward RLIF Training Framework

arXiv:2605.22620v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has substantially improved the reasoning ability of LLMs, but often depends on external supervis

Ultra-High-Definition Image Quality Assessment via Graph Representation Learning

arXiv:2605.22192v1 Announce Type: new Abstract: Blind image quality assessment (BIQA) for ultrahighdefinition (UHD) images remains challenging because native-resolution inference is computationally ex

Understanding Data Temporality Impact on Large Language Models Pre-training

arXiv:2605.22769v1 Announce Type: new Abstract: Large language models (LLMs) are typically trained on shuffled corpora, yielding models whose knowledge is frozen at train time and whose temporal groun

UniVL: Unified Vision-Language Embedding for Spatially Grounded Contextual Image Generation

arXiv:2605.21611v1 Announce Type: new Abstract: We introduce spatially grounded contextual image generation, a controllable image generation task that reframes the conditioning paradigm. Instead of su

VDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents

arXiv:2602.00122v2 Announce Type: replace Abstract: In recent years, image editing models have made significant progress, enabling users to manipulate visual content in a flexible and interactive mann

VEELA: A Clinically-Constrained Benchmark for Liver Vessel Segmentation in Computed Tomography Angiography

arXiv:2605.22357v1 Announce Type: new Abstract: Accurate segmentation of hepatic and portal vessels in contrast-enhanced computed tomography angiography (CTA) remains challenging due to complex vascul

VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis

arXiv:2605.22570v1 Announce Type: new Abstract: Spatio-temporal reasoning is a core capability for Multimodal Large Language Models (MLLMs) operating in the real world. As such, evaluating it precisel

VisPhyWorld: Probing Physical Reasoning via Code-Driven Video Reconstruction

arXiv:2602.13294v3 Announce Type: replace Abstract: Evaluating whether Multimodal Large Language Models (MLLMs) genuinely reason about physical dynamics remains challenging. Most existing benchmarks r

Visual-Advantage On-Policy Distillation for Vision-Language Models

arXiv:2605.21924v1 Announce Type: new Abstract: On-policy knowledge distillation has proven effective for language models, yet its application to vision-language models (VLMs) remains underexplored. W

When Cases Get Rare: A Retrieval Benchmark for Off-Guideline Clinical Question Answering

arXiv:2605.21807v1 Announce Type: new Abstract: Across medical specialties, clinical practice is anchored in evidence-based guidelines that codify best studied diagnostic and treatment pathways. These

X-Token: Projection-Guided Cross-Tokenizer Knowledge Distillation

arXiv:2605.21699v1 Announce Type: cross Abstract: Cross-tokenizer knowledge distillation allows a student model to learn from teachers with incompatible vocabularies. Prior work operates on hidden sta

A Deployment Audit of Release-Side Risk in Conformal Triage under Prevalence Shift

model-releasesarxiv-cs-lg

arXiv:2605.20956v1 Announce Type: new Abstract: Conformal triage converts predictive scores into deployment actions that either release a case, flag it for urgent attention, or defer it to human revie

A Free Lunch in LLM Compression: Revisiting Retraining after Pruning

model-releasesarxiv-cs-lg

arXiv:2510.14444v3 Announce Type: replace Abstract: Post-training pruning can substantially reduce LLM inference costs, but it often degrades quality unless the remaining weights are adapted. Since gl

A strongly annotated passive acoustic dataset for tropical bird monitoring

arXiv:2605.20578v1 Announce Type: cross Abstract: Passive acoustic monitoring enables continuous, non-invasive biodiversity assessment across diverse ecosystems. The scale of these datasets has driven

A Unified Framework for Uncertainty-Aware Explainable Artificial Intelligence: A Case Study in Power Quality Disturbance Classification

model-releasesarxiv-cs-lg

arXiv:2605.21114v1 Announce Type: new Abstract: Post-hoc explainable AI (XAI) methods typically produce deterministic attribution maps, whereas Bayesian neural networks (BNNs) induce a distribution ov