Search: “benchmark”

Boxes2Pixels: Learning Defect Segmentation from Noisy SAM Masks

arXiv:2604.11162v1 Announce Type: new Abstract: Accurate defect segmentation is critical for industrial inspection, yet dense pixel-level annotations are rarely available. A common workaround is to co

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BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning

DGX agent

arXiv:2604.11136v1 Announce Type: cross Abstract: Object-level spatial-temporal understanding is essential for video question answering, yet existing multimodal large language models (MLLMs) encode fr

researcharxiv-cs-ai

14 Apr 2026

Bridging the RGB-IR Gap: Consensus and Discrepancy Modeling for Text-Guided Multispectral Detection

arXiv:2604.11234v1 Announce Type: new Abstract: Text-guided multispectral object detection uses text semantics to guide semantic-aware cross-modal interaction between RGB and IR for more robust percep

safetyarxiv-cs-cv

Bridging What the Model Thinks and How It Speaks: Self-Aware Speech Language Models for Expressive Speech Generation

arXiv:2604.11424v1 Announce Type: new Abstract: Speech Language Models (SLMs) exhibit strong semantic understanding, yet their generated speech often sounds flat and fails to convey expressive intent,

CAGenMol: Condition-Aware Diffusion Language Model for Goal-Directed Molecular Generation

arXiv:2604.11483v1 Announce Type: new Abstract: Goal-directed molecular generation requires satisfying heterogeneous constraints such as protein--ligand compatibility and multi-objective drug-like pro

safetyarxiv-cs-lg

Camyla: Scaling Autonomous Research in Medical Image Segmentation

arXiv:2604.10696v1 Announce Type: new Abstract: We present Camyla, a system for fully autonomous research within the scientific domain of medical image segmentation. Camyla transforms raw datasets int

Applications

Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification?

arXiv:2601.06993v2 Announce Type: replace Abstract: Multi-modal large language models (MLLMs) exhibit strong general-purpose capabilities, yet still struggle on Fine-Grained Visual Classification (FGV

applicationsarxiv-cs-cv

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation

model-releasesarxiv-cs-lg

arXiv:2604.10420v1 Announce Type: new Abstract: Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical questioning, yet most ECG-LLM systems still rely on wea

CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation

arXiv:2604.10504v1 Announce Type: new Abstract: Current large language models (LLMs), even those explicitly trained for reasoning, often struggle with ambiguous content moderation cases due to mislead

Tutorials

CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning

arXiv:2604.10973v1 Announce Type: new Abstract: Reasoning over tabular data is a crucial capability for tasks like question answering and fact verification, as it requires models to comprehend both fr

tutorialsarxiv-cs-ai

Hardware

Characterizing Performance-Energy Trade-offs of Large Language Models in Multi-Request Workflows

arXiv:2604.09611v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in applications forming multi-request workflows like document summarization, search-based copilots,

hardwarearxiv-cs-ai

CircuitSynth: Reliable Synthetic Data Generation

arXiv:2604.10114v1 Announce Type: cross Abstract: The generation of high-fidelity synthetic data is a cornerstone of modern machine learning, yet Large Language Models (LLMs) frequently suffer from ha

researcharxiv-cs-ai

CityGuard: Graph-Aware Private Descriptors for Bias-Resilient Identity Search Across Urban Cameras

arXiv:2602.18047v3 Announce Type: replace Abstract: City-scale person re-identification across distributed cameras must handle severe appearance changes from viewpoint, occlusion, and domain shift whi

safetyarxiv-cs-cv

Class-Adaptive Cooperative Perception for Multi-Class LiDAR-based 3D Object Detection in V2X Systems

arXiv:2604.10305v1 Announce Type: cross Abstract: Cooperative perception allows connected vehicles and roadside infrastructure to share sensor observations, creating a fused scene representation beyon

ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents

arXiv:2604.11784v1 Announce Type: cross Abstract: GUI agents drive applications through their visual interfaces instead of programmatic APIs, interacting with arbitrary software via taps, swipes, and

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation

arXiv:2604.11801v1 Announce Type: new Abstract: With the recent progress of Large Language Models (LLMs), there is a growing interest in applying these models to solve complex and challenging problems

CocoaBench: Evaluating Unified Digital Agents in the Wild

arXiv:2604.11201v1 Announce Type: cross Abstract: LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds a

Local Ai

CodeComp: Structural KV Cache Compression for Agentic Coding

arXiv:2604.10235v1 Announce Type: new Abstract: Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value

local-aiarxiv-cs-cl

CoFusion: Multispectral and Hyperspectral Image Fusion via Spectral Coordinate Attention

arXiv:2604.10584v1 Announce Type: new Abstract: Multispectral and Hyperspectral Image Fusion (MHIF) aims to reconstruct high-resolution images by integrating low-resolution hyperspectral images (LRHSI

Collaborative Multi-Agent Scripts Generation for Enhancing Imperfect-Information Reasoning in Murder Mystery Games

arXiv:2604.11741v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown impressive capabilities in perceptual tasks, yet they degrade in complex multi-hop reasoning under multiplayer

Comparative Analysis of Large Language Models in Healthcare

arXiv:2604.10316v1 Announce Type: new Abstract: Background: Large Language Models (LLMs) are transforming artificial intelligence applications in healthcare due to their ability to understand, generat

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification

model-releasesarxiv-cs-lg

arXiv:2505.11237v3 Announce Type: replace-cross Abstract: Metaphorical imagination, the ability to connect seemingly unrelated concepts, is fundamental to human cognition and communication. While unde

ConceptPose: Training-Free Zero-Shot Object Pose Estimation using Concept Vectors

arXiv:2512.09056v3 Announce Type: replace Abstract: Object pose estimation is a fundamental task in computer vision and robotics, yet most methods require extensive, dataset-specific training. Concurr

Conflicts Make Large Reasoning Models Vulnerable to Attacks

arXiv:2604.09750v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have achieved remarkable performance across diverse domains, yet their decision-making under conflicting objectives rema

Tutorials

Continuous Adversarial Flow Models

arXiv:2604.11521v1 Announce Type: cross Abstract: We propose continuous adversarial flow models, a type of continuous-time flow model trained with an adversarial objective. Unlike flow matching, which

tutorialsarxiv-cs-cv

Controllable and Verifiable Tool-Use Data Synthesis for Agentic Reinforcement Learning

arXiv:2604.09813v1 Announce Type: new Abstract: Existing synthetic tool-use corpora are primarily designed for offline supervised fine-tuning, yet reinforcement learning (RL) requires executable envir

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

safetyarxiv-cs-ai

CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

arXiv:2502.11008v2 Announce Type: replace Abstract: Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this

Cross-Validated Cross-Channel Self-Attention and Denoising for Automatic Modulation Classification

model-releasesarxiv-cs-lg

arXiv:2604.10054v1 Announce Type: new Abstract: This study addresses a key limitation in deep learning Automatic Modulation Classification (AMC) models, which perform well at high signal-to-noise rati

Data-Efficient Semantic Segmentation of 3D Point Clouds via Open-Vocabulary Image Segmentation-based Pseudo-Labeling

arXiv:2604.11007v1 Announce Type: new Abstract: Semantic segmentation of 3D point cloud scenes is a crucial task for various applications. In real-world scenarios, training segmentation models often f

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training

arXiv:2507.15640v2 Announce Type: replace-cross Abstract: Continual pre-training on small-scale task-specific data is an effective method for improving large language models in new target fields, yet

DecAlign: Hierarchical Cross-Modal Alignment for Decoupled Multimodal Representation Learning

arXiv:2503.11892v3 Announce Type: replace Abstract: Multimodal representation learning aims to capture both shared and complementary semantic information across multiple modalities. However, the intri

safetyarxiv-cs-cv

Decoupled Generative Modeling for Human-Object Interaction Synthesis

arXiv:2512.19049v2 Announce Type: replace Abstract: Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control.

Decoupled Similarity for Task-Aware Token Pruning in Large Vision-Language Models

arXiv:2604.11240v1 Announce Type: new Abstract: Token pruning has emerged as an effective approach to reduce the substantial computational overhead of Large Vision-Language Models (LVLMs) by discardin

DeepShapeMatchingKit: Accelerated Functional Map Solver and Shape Matching Pipelines Revisited

arXiv:2604.10377v1 Announce Type: new Abstract: Deep functional maps, leveraging learned feature extractors and spectral correspondence solvers, are fundamental to non-rigid 3D shape matching. Based o

DeepSketcher: Internalizing Visual Manipulation for Multimodal Reasoning

arXiv:2509.25866v2 Announce Type: replace Abstract: The 'thinking with images' paradigm represents a pivotal shift in the reasoning of Vision Language Models (VLMs), moving from text-dominant chain-of

Degradation-Consistent Paired Training for Robust AI-Generated Image Detection

arXiv:2604.10102v1 Announce Type: cross Abstract: AI-generated image detectors suffer significant performance degradation under real-world image corruptions such as JPEG compression, Gaussian blur, an

Delta Rectified Flow Sampling for Text-to-Image Editing

arXiv:2509.05342v3 Announce Type: replace Abstract: We propose Delta Rectified Flow Sampling (DRFS), a novel inversion-free, path-aware editing framework within rectified flow models for text-to-image

Design Principles for Sequence Models via Coefficient Dynamics

arXiv:2510.09389v2 Announce Type: replace-cross Abstract: Deep sequence models, ranging from Transformers and State Space Models (SSMs) to more recent approaches such as gated linear RNNs, fundamental

Detecting Corporate AI-Washing via Cross-Modal Semantic Inconsistency Learning

arXiv:2604.09644v1 Announce Type: cross Abstract: Corporate AI-washing-the strategic misrepresentation of AI capabilities via exaggerated or fabricated cross-channel disclosures-has emerged as a syste

Detecting Safety Violations Across Many Agent Traces

arXiv:2604.11806v1 Announce Type: new Abstract: To identify safety violations, auditors often search over large sets of agent traces. This search is difficult because failures are often rare, complex,

Detection Is Cheap, Routing Is Learned: Why Refusal-Based Alignment Evaluation Fails

arXiv:2603.18280v2 Announce Type: replace-cross Abstract: Current alignment evaluation mostly measures whether models encode dangerous concepts and whether they refuse harmful requests. Both miss the

safetyarxiv-cs-ai

Development and evaluation of CADe systems in low-prevalence setting: The RARE25 challenge for early detection of Barrett's neoplasia

arXiv:2604.11171v1 Announce Type: new Abstract: Computer-aided detection (CADe) of early neoplasia in Barrett's esophagus is a low-prevalence surveillance problem in which clinically relevant findings

DINO_4D: Semantic-Aware 4D Reconstruction

arXiv:2604.09877v1 Announce Type: cross Abstract: In the intersection of computer vision and robotic perception, 4D reconstruction of dynamic scenes serve as the critical bridge connecting low-level g

researcharxiv-cs-ai

DisCo-FLoc: Using Dual-Level Visual-Geometric Contrasts to Disambiguate Depth-Aware Visual Floorplan Localization

arXiv:2601.01822v2 Announce Type: replace-cross Abstract: Since floorplan data is readily available, long-term persistent, and robust to changes in visual appearance, visual Floorplan Localization (FL

Discrete Bayesian Sample Inference for Graph Generation

arXiv:2511.03015v2 Announce Type: replace Abstract: Generating graph-structured data is crucial in applications such as molecular generation, knowledge graphs, and network analysis. However, their dis

researcharxiv-cs-lg

DiSPA: Differential Substructure-Pathway Attention for Drug Response Prediction

arXiv:2601.14346v2 Announce Type: replace-cross Abstract: Accurate prediction of drug response in precision medicine requires models that capture how specific chemical substructures interact with cell

Distributionally Robust K-Means Clustering

arXiv:2604.11118v1 Announce Type: new Abstract: K-means clustering is a workhorse of unsupervised learning, but it is notoriously brittle to outliers, distribution shifts, and limited sample sizes. Vi

researcharxiv-cs-lg