Search: “framework”

BARD: Bridging AutoRegressive and Diffusion Vision-Language Models Via Highly Efficient Progressive Block Merging and Stage-Wise Distillation

arXiv:2604.16514v1 Announce Type: new Abstract: Autoregressive vision-language models (VLMs) deliver strong multimodal capability, but their token-by-token decoding imposes a fundamental inference bot

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Batch-Adaptive Causal Annotations

DGX agent

arXiv:2502.10605v3 Announce Type: replace-cross Abstract: Estimating the causal effects of interventions is crucial to policy and decision-making, yet outcome data are often missing or subject to non-

safetyarxiv-cs-lg

21 Apr 2026

Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report

arXiv:2604.17707v1 Announce Type: new Abstract: Clinical personality assessment screens response validity before interpreting substantive scales. LLM evaluation does not. We apply the validity scaling

Benchmarking programs?

The Reddit post 'Benchmarking programs?' in r/ollama likely discusses tools and methods for measuring the performance of local language models running on Ollama. Available benchmarking tools for Ollam

local-air-ollama

Benchmarking Real-Time Question Answering via Executable Code Workflows

arXiv:2604.16349v1 Announce Type: cross Abstract: Retrieving real-time information is a fundamental capability for search-integrated agents in real-world applications. However, existing benchmarks are

BengaliMoralBench: A Benchmark for Auditing Moral Reasoning in Large Language Models within Bengali Language and Culture

arXiv:2511.03180v2 Announce Type: replace Abstract: As multilingual Large Language Models (LLMs) gain traction across South Asia, their alignment with local ethical norms, particularly for Bengali, sp

Tutorials

Beyond Attack Success Rate: A Multi-Metric Evaluation of Adversarial Transferability in Medical Imaging Models

arXiv:2604.16532v1 Announce Type: new Abstract: While deep learning systems are becoming increasingly prevalent in medical image analysis, their vulnerabilities to adversarial perturbations raise seri

tutorialsarxiv-cs-cv

Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors

arXiv:2604.17914v1 Announce Type: new Abstract: Self-supervised contrastive learning has emerged as a powerful paradigm for skeleton-based action recognition by enforcing consistency in the embedding

Beyond Fine-Tuning: In-Context Learning and Chain-of-Thought for Reasoned Distractor Generation

arXiv:2604.17574v1 Announce Type: new Abstract: Distractor generation (DG) remains a labor-intensive task that still significantly depends on domain experts. The task focuses on generating plausible y

Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling

arXiv:2508.16745v2 Announce Type: replace Abstract: Reasoning is a core capability of large language models, yet how multi-step reasoning is learned and executed remains unclear. We study this questio

local-aiarxiv-cs-lg

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BIASEDTALES-ML: A Multilingual Dataset for Analyzing Narrative Attribute Distributions in LLM-Generated Stories

arXiv:2604.17008v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate narrative content, including children's stories, which play an important role in social a

safetyarxiv-cs-cl

BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs

arXiv:2604.17629v1 Announce Type: new Abstract: Pretrained biomedical vision-language models (VLMs) such as BioMedCLIP perform well on average but often degrade on challenging modalities where inter-c

BOOKAGENT: Orchestrating Safety-Aware Visual Narratives via Multi-Agent Cognitive Calibration

arXiv:2604.16541v1 Announce Type: new Abstract: Recent advancements in Large Generative Models (LGMs) have revolutionized multi-modal generation. However, generating illustrated storybooks remains an

Bounded Graph Clustering with Graph Neural Networks

arXiv:2512.05623v2 Announce Type: replace Abstract: In community detection, many methods require the user to specify the number of clusters in advance since an exhaustive search over all possible valu

researcharxiv-cs-lg

Agents

BrainMem: Brain-Inspired Evolving Memory for Embodied Agent Task Planning

arXiv:2604.16331v1 Announce Type: cross Abstract: Embodied task planning requires agents to execute long-horizon, goal-directed actions in complex 3D environments, where success depends on both immedi

agentsarxiv-cs-cv

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BRIDGE the Gap: Mitigating Bias Amplification in Automated Scoring of English Language Learners via Inter-group Data Augmentation

arXiv:2602.23580v2 Announce Type: replace Abstract: In the field of educational assessment, automated scoring systems increasingly rely on deep learning and large language models (LLMs). However, thes

safetyarxiv-cs-cl

Bridging Coarse and Fine Recognition: A Hybrid Approach for Open-Ended Multi-Granularity Object Recognition in Interactive Educational Games

arXiv:2604.16785v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have enabled open-ended object recognition, yet they struggle with fine-grained tasks. In co

Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling

arXiv:2604.17794v1 Announce Type: new Abstract: The democratization of ubiquitous AI hinges on deploying sophisticated reasoning capabilities on resource-constrained devices. However, Small Language M

Budget-Aware Anytime Reasoning with LLM-Synthesized Preference Data

arXiv:2601.11038v2 Announce Type: replace Abstract: We study the reasoning behavior of large language models (LLMs) under limited computation budgets. In such settings, producing useful partial soluti

Tutorials

CAARL: In-Context Learning for Interpretable Co-Evolving Time Series Forecasting

arXiv:2604.18305v1 Announce Type: new Abstract: In this paper we investigate forecasting coevolving time series that feature intricate dependencies and nonstationary dynamics by using an LLM Large Lan

tutorialsarxiv-cs-lg

Calibrating Model-Based Evaluation Metrics for Summarization

arXiv:2604.17200v1 Announce Type: new Abstract: Recent advances in summary evaluation are based on model-based metrics to assess quality dimensions, such as completeness, conciseness, and faithfulness

CAM3DNet: Comprehensively mining the multi-scale features for 3D Object Detection with Multi-View Cameras

arXiv:2604.17024v1 Announce Type: new Abstract: Query-based 3D object detection methods using multi-view images often struggle to efficiently leverage dynamic multi-scale information, e.g., the relati

Camo-M3FD: A New Benchmark Dataset for Cross-Spectral Camouflaged Pedestrian Detection

arXiv:2604.16582v1 Announce Type: new Abstract: Pedestrian detection is fundamental to autonomous driving, robotics, and surveillance. Despite progress in deep learning, reliable identification remain

CamPVG: Camera-Controlled Panoramic Video Generation with Epipolar-Aware Diffusion

arXiv:2509.19979v2 Announce Type: replace Abstract: Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing meth

Can LLM-Generated Text Empower Surgical Vision-Language Pre-training?

arXiv:2604.18134v1 Announce Type: new Abstract: Recent advancements in self-supervised learning have led to powerful surgical vision encoders capable of spatiotemporal understanding. However, extendin

Applications

CanonSLR: Canonical-View Guided Multi-View Continuous Sign Language Recognition

arXiv:2604.18184v1 Announce Type: new Abstract: Continuous Sign Language Recognition (CSLR) has achieved remarkable progress in recent years; however, most existing methods are developed under single-

applicationsarxiv-cs-cv

CATP: Confidence-Aware Token Pruning for Camouflaged Object Detection

arXiv:2604.16854v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to segment targets that share extreme textural and structural similarities with their complex environments. Leve

Causally-Constrained Probabilistic Forecasting for Time-Series Anomaly Detection

arXiv:2604.17998v1 Announce Type: new Abstract: Anomaly detection in multivariate time series is a central challenge in industrial monitoring, as failures frequently arise from complex temporal dynami

local-aiarxiv-cs-lg

CBRS: Cognitive Blood Request System with Bilingual Dataset and Dual-Layer Filtering for Multi-Platform Social Streams

arXiv:2604.16665v1 Announce Type: new Abstract: Urgent blood donation seeking posts and messages on social media often go unnoticed due to the overwhelming volume of daily communications. Traditional

CDSA-Net:Collaborative Decoupling of Vascular Structure and Background for High-Fidelity Coronary Digital Subtraction Angiography

arXiv:2604.17208v1 Announce Type: new Abstract: Digital subtraction angiography (DSA) in coronary imaging is fundamentally challenged by physiological motion, forcing reliance on raw angiograms clutte

CFMS: Towards Explainable and Fine-Grained Chinese Multimodal Sarcasm Detection Benchmark

arXiv:2604.16372v1 Announce Type: new Abstract: Multimodal sarcasm detection has recently garnered significant attention. However, existing benchmarks suffer from coarse-grained annotations and limite

CFSR: Geometry-Conditioned Shadow Removal via Physical Disentanglement

arXiv:2604.18032v1 Announce Type: new Abstract: Traditional shadow removal networks often treat image restoration as an unconstrained mapping, lacking the physical interpretability required to balance

local-aiarxiv-cs-cv

CLASP: Training-Free LLM-Assisted Source Code Watermarking via Semantic-Preserving Transformations

arXiv:2510.11251v2 Announce Type: replace-cross Abstract: The proliferation of open-source code and large language models (LLMs) for code generation has amplified the risks of unauthorized reuse and i

local-aiarxiv-cs-lg

ClawEnvKit: Automatic Environment Generation for Claw-Like Agents

arXiv:2604.18543v1 Announce Type: cross Abstract: Constructing environments for training and evaluating claw-like agents remains a manual, human-intensive process that does not scale. We argue that wh

CoAct: Co-Active LLM Preference Learning with Human-AI Synergy

arXiv:2604.17501v1 Announce Type: new Abstract: Learning from preference-based feedback has become an effective approach for aligning LLMs across diverse tasks. However, high-quality human-annotated p

CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora

arXiv:2604.18027v1 Announce Type: cross Abstract: Transpilation, or code translation, aims to convert source code from one programming language (PL) to another. It is beneficial for many downstream ap

Coevolving Representations in Joint Image-Feature Diffusion

arXiv:2604.17492v1 Announce Type: new Abstract: Joint image-feature generative modeling has recently emerged as an effective strategy for improving diffusion training by coupling low-level VAE latents

Agents

CogDriver: Integrating Cognitive Inertia for Temporally Coherent Planning in Autonomous Driving

arXiv:2509.00789v2 Announce Type: replace Abstract: The pursuit of autonomous agents capable of temporally coherent planning is hindered by a fundamental flaw in current vision-language models (VLMs):

agentsarxiv-cs-cv

Cognitive Chain-of-Thought (CoCoT): Structured Multimodal Reasoning about Social Situations

arXiv:2507.20409v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting helps models think step by step. But naive CoT breaks down in visually grounded social tasks, where models must per

Tutorials

CoGR-MoE: Concept-Guided Expert Routing with Consistent Selection and Flexible Reasoning for Visual Question Answering

arXiv:2604.16930v1 Announce Type: new Abstract: Visual Question Answering (VQA) requires models to identify the correct answer options based on both visual and textual evidence. Recent Mixture-of-Expe

tutorialsarxiv-cs-cv

Compiling OpenSCENARIO 2.1 for Scenario-Based Testing in CARLA

arXiv:2604.16452v1 Announce Type: new Abstract: While the ASAM OpenSCENARIO 2.1 Domain-Specific Language (DSL) enables declarative, intent-driven authoring for Scenario-Based Testing (SBT), its integr

researcharxiv-cs-ro

Complex normalizing flows can be information Kahler-Ricci flows

model-releasesarxiv-cs-lg

arXiv:2604.17954v1 Announce Type: cross Abstract: We develop interconnections between the complex normalizing flow for data drawn from Borel probability measures on the twofold realification of the co

Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2604.17616v1 Announce Type: new Abstract: Root cause analysis (RCA) for time-series anomaly detection is critical for the reliable operation of complex real-world systems. Existing explanation m

Context Matters: Peer-Aware Student Behavioral Engagement Measurement via VLM Action Parsing and LLM Sequence Classification

arXiv:2601.06394v3 Announce Type: replace Abstract: Understanding student behavior in the classroom is essential to improve both pedagogical quality and student engagement. Existing methods for predic

Continuous Limits of Coupled Flows in Representation Learning

model-releasesarxiv-cs-lg

arXiv:2604.16801v1 Announce Type: new Abstract: While modern representation learning relies heavily on global error signals, decentralized algorithms driven by local interactions offer a fundamental d

Applications

Contraction and Hourglass Persistence for Learning on Graphs, Simplices, and Cells

arXiv:2604.17548v1 Announce Type: new Abstract: Persistent homology (PH) encodes global information, such as cycles, and is thus increasingly integrated into graph neural networks (GNNs). PH methods i

applicationsarxiv-cs-lg

Safety

COSEARCH: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search

arXiv:2604.17555v1 Announce Type: cross Abstract: Agentic search -- the task of training agents that iteratively reason, issue queries, and synthesize retrieved information to answer complex questions

safetyarxiv-cs-cl

Applications

Covariance-Based Structural Equation Modeling in Small-Sample Settings with p>n

arXiv:2604.16894v1 Announce Type: new Abstract: Factor-based Structural Equation Modeling (SEM) relies on likelihood-based estimation assuming a nonsingular sample covariance matrix, which breaks down

applicationsarxiv-cs-lg