Search: “benchmark”

Adapting Vision-Language Models for Human-Readable XAI in Industrial Object Detection

arXiv:2609.31690v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) solutions are essential for building trust in AI technologies and their integration in real manufacturing line

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Adaptive Ensemble Selection for Noisy Labels on Tabular Data

DGX agent

arXiv:2609.32976v1 Announce Type: new Abstract: Incorrect or corrupted labels in tabular datasets can significantly degrade supervised learning performance, particularly when mislabeling is subtle and

model-releasesarxiv-cs-lg

29 Sept 2026

Tutorials

Addressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Masking

arXiv:2609.35021v1 Announce Type: new Abstract: Spatiotemporal prediction aims to learn discriminative representations from correlated temporal signals over spatial structures for accurate future infe

tutorialsarxiv-cs-lg

Advancing Video-Text Pretraining with Multi-View Captions

arXiv:2609.35090v1 Announce Type: new Abstract: Video-text pretraining has achieved remarkable progress through the scaling of models and datasets, yet the quality of language supervision remains unde

Adversarial Consistency-Guided Representation Learning for Multi-view Clustering

arXiv:2609.35212v1 Announce Type: new Abstract: Multi-view clustering aims to capture cross-view consistency while exploiting view-specific information. However, shared representations learned to capt

Agents

Agentic High-Dimensional Bayesian Optimization with Hypothesis- and Evidence-Guided Search

arXiv:2609.34281v1 Announce Type: new Abstract: High-dimensional Bayesian optimization (HDBO) seeks sample-efficient optimization when the number of variables is large relative to the evaluation budge

agentsarxiv-cs-lg

Agentic Multi-Turn Reasoning: A Fairness Approach

arXiv:2609.33323v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems capable of solving complex tasks through multi-turn planning, tool use, v

Agents

Agentic Video Understanding: A Survey

arXiv:2609.31713v1 Announce Type: new Abstract: As large language models (LLMs) become capable of processing increasingly diverse modalities and longer temporal contexts, an emerging line of work is m

agentsarxiv-cs-cv

Agents

AgentWare: Automating the Lifecycle of Agentic Applications across the Edge-to-Cloud Continuum

arXiv:2609.34586v1 Announce Type: cross Abstract: Deploying LLM-enabled agentic applications across the Edge-to-Cloud continuum remains challenging due to hardware heterogeneity, deployment complexity

agentsarxiv-cs-lg

AGILE-GS: Anchor-Guided Fast Next-Best-View Selection for Active 3D Gaussian Splatting

arXiv:2609.34176v1 Announce Type: new Abstract: Radiance fields need hundreds of views, and their placement matters as much as their number. Next-best-view (NBV) selection for 3D Gaussian Splatting (3

AI-driven Dispensing of Coral Reseeding Devices for Broad-scale Restoration of the Great Barrier Reef

arXiv:2509.01019v3 Announce Type: replace Abstract: Coral reefs are on the brink of collapse, with climate change, ocean acidification, and pollution leading to a projected 70-90% loss of coral specie

ALDER: Discovering the Laws of a World by Acting in It

arXiv:2609.33728v1 Announce Type: new Abstract: Reliable world models should not only predict future states but express how actions change the world in an explicit, transparent and testable form, such

ALICE: In-context, Zero-shot, Mutual Information Estimation

arXiv:2609.34962v1 Announce Type: new Abstract: Estimating mutual information (MI) from samples is a central objective in a variety of scientific fields. Modern neural estimators are accurate in the l

Alignment-Guided Flow Transformer for Efficient Vision-Language-Action Policy Learning

arXiv:2609.34467v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models point toward general-purpose robotic intelligence by unifying perception, instruction, and contro

An RL View of OPD: Least Square Policy Distillation for Sample-Efficient LLM Reasoning

arXiv:2609.35505v1 Announce Type: new Abstract: We study on-policy distillation (OPD) through the lens of reinforcement learning, establishing a connection between the reverse-KL objective in OPD and

Analytic-Walk Rotary Positional Encodings for Graphs

arXiv:2609.32178v1 Announce Type: new Abstract: Rotary position encodings make attention sensitive to relative position, but extending them to graphs requires choosing how graph structure enters the r

Annealed Sinkhorn with Momentum: Certified Unregularized Optimal Transport in Linear Memory

arXiv:2609.33814v1 Announce Type: cross Abstract: We characterize Bregman Douglas-Rachford splitting (BDRS) for unregularized discrete optimal transport and develop an anytime primal-dual certificate

AquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2609.33299v1 Announce Type: new Abstract: World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequence

Attention Graphons: A Graph Limit Perspective on Graph Transformers

arXiv:2609.35620v1 Announce Type: new Abstract: Graph Transformers produce, for each attention head, a dense nimes n matrix of learned pairwise interactions. We ask a fundamental question: do these at

AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs

arXiv:2509.25570v2 Announce Type: replace Abstract: Vision Graph Neural Networks (ViGs) have demonstrated promising performance in image recognition tasks against Convolutional Neural Networks (CNNs)

Audit-First VAPO: Risk-Certified Selective Updates under Imperfect Verification

arXiv:2609.33662v1 Announce Type: cross Abstract: Imperfect verifiers can assign a harmful update direction even when clipping and regularization bound its magnitude. We introduce Audit-First VAPO, wh

Tutorials

Augmenting Visual Anomaly Detection with Automated Interpretability

arXiv:2609.33818v1 Announce Type: new Abstract: Visual anomaly detectors identify deviations from known-normal data, but their anomaly signals may mix evidence of actual anomalies with benign visual v

tutorialsarxiv-cs-cv

AutoHGNN: Robust and Efficient Neural Architecture Search for Hypergraph Neural Networks

arXiv:2609.33392v1 Announce Type: new Abstract: Hypergraph neural networks have achieved significant success in recent years. However, manual architecture crafting is labor-intensive and often fails t

Autonomous phase discovery

arXiv:2609.33802v1 Announce Type: cross Abstract: Understanding quantum phases of matter has long relied on physicists' intuition and mathematical tools such as symmetry and topology. Remarkably succe

Applications

AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists

arXiv:2506.08140v2 Announce Type: replace Abstract: Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-qualit

applicationsarxiv-cs-lg

Backdoor as Probe: Test-Time Adversarial Defense for CLIP

arXiv:2609.34641v1 Announce Type: new Abstract: Test-time adversarial defense improves the robustness of vision-language foundation models such as CLIP without retraining. However, adversarial activat

Behavioral Foundation Models for Quality Diversity

arXiv:2609.35615v1 Announce Type: new Abstract: Behavioral Foundation Models (BFMs) are an emerging paradigm in reinforcement learning, playing a role analogous to large language models in natural lan

BERT4DTI : BERT-based Model for Predicting Drug-Protein Interactions

arXiv:2609.33254v1 Announce Type: new Abstract: Understanding how drugs interact with protein targets is fundamental to drug discovery, drug repurposing and the early identification of promising thera

Beyond Gradient Flow: Identifiability and Recovery from Distribution Snapshots

arXiv:2609.35060v1 Announce Type: new Abstract: Inferring dynamics from snapshots of evolving distributions is fundamentally underdetermined: the Fokker-Planck equation constrains the drift F only thr

Beyond Isolated Entities: Relation-Aware Multi-Entity Modeling for Unsupervised Video Anomaly Detection

arXiv:2609.31753v1 Announce Type: cross Abstract: Video anomaly detection for patrol robots and surveillance systems must recognize abnormal interactions among familiar entities. Existing pixel-recons

Beyond One Epoch: Uncertainty-Weighted Sensitivity Regularization for Recommendation Models

arXiv:2609.34083v1 Announce Type: new Abstract: Recommendation models with sparse embeddings and a shared consumer often exhibit the one-epoch phenomenon: a second epoch lowers training loss while sha

Beyond Teacher Assignment: Domain-Normalized Multi-Teacher On-Policy Distillation

arXiv:2609.35347v1 Announce Type: new Abstract: Reinforcement learning can turn one language model into several specialists, each excellent at a single skill such as mathematics, coding or following i

Beyond Volume Overlap: Surface Matching for Topology-Aware Coronary Artery Segmentation

arXiv:2609.31740v1 Announce Type: new Abstract: Accurate coronary artery segmentation on coronary computed tomography angiography (CCTA) is essential for diagnosing coronary artery disease. Deep netwo

BiasReducer: Adaptive Bias Mitigation for Reward Models

arXiv:2609.32720v1 Announce Type: new Abstract: Reward models score responses from large language models (LLMs) and guide LLM training toward human preferences. However, reward models can favor superf

Bidirectional Information Flow (BIF) - A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization

arXiv:2505.11294v3 Announce Type: replace Abstract: Hierarchical Gaussian Process (H-GP) models divide problems into different subtasks, allowing different components to address each part, making them

Bridging Generative and Discriminative Noisy-Label Learning via Direction-Agnostic EM Formulation

arXiv:2308.01184v4 Announce Type: replace Abstract: Although noisy-label learning is often approached with discriminative methods for simplicity and speed, generative modeling offers a principled alte

safetyarxiv-cs-cv

CAESAR: Clustering via Autonomous Embedding-Space Agglomerative Reorganization

arXiv:2609.32570v1 Announce Type: new Abstract: Clustering algorithms that operate on nearest-neighbor graphs, such as FINCH (First Integer Neighbor Clustering Hierarchy), depend heavily on the qualit

CalibHyper: Chance-Corrected Relational Hypergraphs for Few-Shot Molecular Property Prediction

arXiv:2609.33342v1 Announce Type: new Abstract: Molecular property prediction is central to drug development and materials discovery, but experiments are costly and labeled data are scarce. Context-aw

Can Circuit Alignment Predict OOD Generalization?

arXiv:2609.31996v1 Announce Type: new Abstract: Can out-of-distribution (OOD) generalization be predicted from a trained model's weights alone, without any target-domain data? Existing representationa

Can Tabular Foundation Models Amortize Statistical Inference?

arXiv:2609.33114v1 Announce Type: cross Abstract: For decades, statistical inference has largely been developed one problem at a time. Given a scientific target, such as a treatment effect or a regres

Can't Find Waldo: Evaluating VLMs' Sensitivity to Image Resolution and Detail Level

arXiv:2609.31706v1 Announce Type: new Abstract: Visual Language Models (VLMs) have achieved remarkable success across diverse tasks, yet they struggle with high-resolution inputs where critical inform

CaptchaArena: A Large-Scale, Fine-Grained Dataset for Training Computer-Use Agents on Interactive CAPTCHAs

arXiv:2609.31957v1 Announce Type: new Abstract: Interactive CAPTCHAs remain challenging for computer-use agents, while existing datasets face trade-offs among type coverage, interaction fidelity, and

safetyarxiv-cs-cv

CarveMix-RC: Addressing Rare-Class Imbalance Through Lesion-Aware Synthetic Augmentation for Brain Metastasis Segmentation

arXiv:2609.35195v1 Announce Type: new Abstract: Accurate segmentation of post-treatment brain metastases is essential for treatment planning, longitudinal disease monitoring, and quantitative assessme

Tutorials

CasEm: A Cascade Architecture for Long-Horizon Neural Emulation

arXiv:2609.34246v1 Announce Type: new Abstract: Autoregressive neural emulators can drift or diverge over long rollouts despite accurate short-term predictions. We introduce Cascaded Emulation (CasEm)

tutorialsarxiv-cs-lg

CFLoRA: Federated Fine-tuning of LLMs with Complementary Factors for Error-free Aggregation

arXiv:2609.33147v1 Announce Type: new Abstract: Federated low-rank adaptation (LoRA) enables collaborative fine-tuning of large language models without centralizing private client data. Its factorized

CoCurve: Cross-Module Co-Pruning Curvature for Structured LLM Pruning

arXiv:2607.17568v2 Announce Type: replace Abstract: Resource-constrained deployment requires sustaining large language model (LLM) capabilities as models scale under fixed memory and computation budge

CodeActionBench: Evaluating Agentic Code-as-Policy for Embodied Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.33807v1 Announce Type: new Abstract: How well can general-purpose multimodal models turn visual understanding and reasoning into embodied manipulation via executable code? We introduce Code

CoDrive: Cross-Vehicle World-Consistent Video Generation with Precise Trajectory Control for Cooperative Driving

arXiv:2609.34749v1 Announce Type: new Abstract: Real-world driving is inherently multi-agent, yet most existing driving world models generate observations from a single ego vehicle. Independently exte