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arXiv:2604.26940v1 Announce Type: new Abstract: Small language models (SLMs) offer computational efficiency for scalable deployment, yet they often fall short of the reasoning power exhibited by their

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SkyReels-Text: Fine-Grained Font-Controllable Text Editing for Poster Design

DGX agent

arXiv:2511.13285v2 Announce Type: replace Abstract: Artistic design, particularly poster design, often demands rapid yet precise modification of textual content while preserving visual harmony and typ

researcharxiv-cs-cv

30 Apr 2026

SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses

arXiv:2604.26620v1 Announce Type: new Abstract: Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in th

researcharxiv-cs-cv

Sparsity as a Key: Unlocking New Insights from Latent Structures for Out-of-Distribution Detection

arXiv:2604.26409v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) have demonstrated significant success in interpreting Large Language Models (LLMs) by decomposing dense representations into

safetyarxiv-cs-cv

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness

arXiv:2604.26341v1 Announce Type: new Abstract: Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image

researcharxiv-cs-cv

SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning

arXiv:2604.26388v1 Announce Type: cross Abstract: Federated Split Learning has been identified as an efficient approach to address the computational resource constraints of clients in classical federa

applicationsarxiv-cs-lg

StarDrinks: An English and Korean Test Set for SLU Evaluation in a Drink Ordering Scenario

arXiv:2604.26500v1 Announce Type: new Abstract: LLMs and speech assistants are increasingly used for task-oriented interactions, yet their evaluation often relies on controlled scenarios that fail to

Stress Testing Factual Consistency Metrics for Long-Document Summarization

arXiv:2511.07689v2 Announce Type: replace-cross Abstract: Evaluating the factual consistency of abstractive text summarization remains a significant challenge, particularly for long documents, where c

Structural Generalization on SLOG without Hand-Written Rules

arXiv:2604.26157v1 Announce Type: cross Abstract: Structural generalization in semantic parsing requires systems to apply learned compositional rules to novel structural combinations. Existing approac

SWE-Edit: Rethinking Code Editing for Efficient SWE-Agent

arXiv:2604.26102v1 Announce Type: cross Abstract: Large language model agents have achieved remarkable progress on software engineering tasks, yet current approaches suffer from a fundamental context

Local Ai

Tell Model Where to Look: Mitigating Hallucinations in MLLMs by Vision-Guided Attention

arXiv:2511.20032v3 Announce Type: replace Abstract: Visual attention serves as the primary mechanism through which MLLMs interpret visual information; however, its limited localization capability ofte

local-aiarxiv-cs-cv

Test-Time Safety Alignment

arXiv:2604.26167v1 Announce Type: cross Abstract: Recent work has shown that a model's input word embeddings can serve as effective control variables for steering its behavior toward outputs that sati

safetyarxiv-cs-ai

The Unseen Adversaries: Robust and Generalized Defense Against Adversarial Patches

model-releasesarxiv-cs-cv

arXiv:2604.26317v1 Announce Type: new Abstract: The vulnerabilities of deep neural networks against singularities have raised serious concerns regarding their deployment in the physical world. One of

Thinking with Drafting: Optical Decompression via Logical Reconstruction

arXiv:2602.11731v2 Announce Type: replace Abstract: Existing multimodal large language models have achieved high-fidelity visual perception and exploratory visual generation. However, a precision para

TildeOpen LLM: Leveraging Curriculum Learning to Achieve Equitable Language Representation

arXiv:2603.08182v2 Announce Type: replace-cross Abstract: Large language models often underperform in many European languages due to the dominance of English and a few high-resource languages in train

Time Blindness: Why Video-Language Models Can't See What Humans Can?

arXiv:2505.24867v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have made impressive strides in understanding spatio-temporal relationships in videos. Howeve

Time series classification with random convolution kernels: pooling operators and input representations matter

arXiv:2409.01115v5 Announce Type: replace Abstract: This article presents a new approach based on MiniRocket, called SelF-Rocket, for fast time series classification (TSC). Unlike existing approaches

TimeMM: Time-as-Operator Spectral Filtering for Dynamic Multimodal Recommendation

arXiv:2604.26247v1 Announce Type: cross Abstract: Multimodal recommendation improves user modeling by integrating collaborative signals with heterogeneous item content. In real applications, user inte

applicationsarxiv-cs-ai

TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation

arXiv:2503.04872v3 Announce Type: replace-cross Abstract: The challenge of reducing the size of Large Language Models (LLMs) while maintaining their performance has gained significant attention. Howev

ToolPRM: Fine-Grained Inference Scaling of Structured Outputs for Function Calling

arXiv:2510.14703v2 Announce Type: replace Abstract: Large language models (LLMs) excel at function calling, but inference scaling has been explored mainly for unstructured generation. We propose an in

Turning the TIDE: Cross-Architecture Distillation for Diffusion Large Language Models

arXiv:2604.26951v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer parallel decoding and bidirectional context, but state-of-the-art dLLMs require billions of parameters f

Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics

arXiv:2604.26836v1 Announce Type: new Abstract: Predictive safety filters (PSFs) leverage model predictive control to enforce constraint satisfaction during deep reinforcement learning (RL) exploratio

safetyarxiv-cs-lg

Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

arXiv:2604.26694v1 Announce Type: cross Abstract: We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruc

VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models

arXiv:2505.22897v2 Announce Type: replace Abstract: While bias in large language models (LLMs) is well-studied, similar concerns in vision-language models (VLMs) have received comparatively less atten

VLN-Cache: Enabling Token Caching for VLN Models with Visual/Semantic Dynamics Awareness

arXiv:2603.07080v3 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) increasingly relies on large vision-language models, but their inference cost conflicts with real-time de

WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models

arXiv:2510.14438v2 Announce Type: replace Abstract: The hallmark of Deep Research agents lies in compositional reasoning, the capacity to aggregate distributed, heterogeneous information into coherent

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling

arXiv:2604.26644v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on mathematical reasoning tasks but remain unreliable on challenging instances. Existing test-t

Why Attend to Everything? Focus is the Key

arXiv:2604.03260v2 Announce Type: replace-cross Abstract: Standard attention scales quadratically with sequence length. Efficient attention methods reduce this O(n^2) cost, but when retrofitted into p

A Comparative Analysis on the Performance of Upper Confidence Bound Algorithms in Adaptive Deep Neural Networks

arXiv:2604.24810v1 Announce Type: new Abstract: Edge computing environments impose strict constraints on energy consumption and latency, making the deployment of deep neural networks a significant cha

A systematic literature Review for Transformer-based Software Vulnerability detection

arXiv:2604.24822v1 Announce Type: cross Abstract: Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas

applicationsarxiv-cs-lg

Adaptable phase retrieval for coherent transition radiation spectroscopy based on differentiable physics information

arXiv:2604.25489v1 Announce Type: cross Abstract: Coherent transition radiation (CTR) spectroscopy is a critical diagnostic for characterizing the longitudinal structure of relativistic electron bunch

ADE: Adaptive Dictionary Embeddings -- Scaling Multi-Anchor Representations to Large Language Models

arXiv:2604.24940v1 Announce Type: new Abstract: Word embeddings are fundamental to natural language processing, yet traditional approaches represent each word with a single vector, creating representa

Agents

Agentic AI for Remote Sensing: Technical Challenges and Research Directions

arXiv:2604.24919v1 Announce Type: new Abstract: Earth Observation (EO) is moving beyond static prediction toward multi-step analytical workflows that require coordinated reasoning over data, tools, an

agentsarxiv-cs-cv

Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses

arXiv:2604.25850v1 Announce Type: new Abstract: Harnesses have become a central determinant of coding-agent performance, shaping how models interact with repositories, tools, and execution environment

Analyzing LLM Reasoning to Uncover Mental Health Stigma

arXiv:2604.25053v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly being explored for mental health applications, recent studies reveal that they can exhibit stigma to

Application of a Mixture of Experts-based Foundation Model to the GlueX DIRC Detector

arXiv:2604.24775v1 Announce Type: cross Abstract: We present a Mixture-of-Experts-based foundation model applied to the GlueX DIRC detector at Jefferson Lab, demonstrating its utility as a unified fra

ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs

arXiv:2410.24214v3 Announce Type: replace-cross Abstract: Mixed precision quantization has become an important technique for optimizing the execution of deep neural networks (DNNs). Certified robustne

researcharxiv-cs-cv

asRoBallet: Closing the Sim2Real Gap via Friction-Aware Reinforcement Learning for Underactuated Spherical Dynamics

model-releasesarxiv-cs-ro

arXiv:2604.24916v1 Announce Type: new Abstract: We introduce asRoBallet, to the best of our knowledge, the first successful deployment of reinforcement learning (RL) on a humanoid ballbot hardware. Hi

Backtranslation Augmented Direct Preference Optimization for Neural Machine Translation

arXiv:2604.25702v1 Announce Type: new Abstract: Contemporary neural machine translation (NMT) systems are almost exclusively built by training on supervised parallel data. Despite the tremendous progr

researcharxiv-cs-cl

BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

model-releasesarxiv-cs-cv

arXiv:2604.24999v1 Announce Type: new Abstract: Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understa

BLASST: Dynamic BLocked Attention Sparsity via Softmax Thresholding

arXiv:2512.12087v3 Announce Type: replace Abstract: The growing demand for long-context inference capabilities in Large Language Models (LLMs) has intensified the computational and memory bottlenecks

Bye Bye Perspective API: Lessons for Measurement Infrastructure in NLP, CSS and LLM Evaluation

arXiv:2604.25580v1 Announce Type: new Abstract: The closure of Perspective API at the end of 2026 discards what has functioned as the de facto standard for automated toxicity measurement in NLP, CSS,

researcharxiv-cs-cl

Cheaper, Better, Faster, Stronger: Robust Text-to-SQL without Chain-of-Thought or Fine-Tuning

arXiv:2505.14174v2 Announce Type: replace Abstract: LLMs are effective at code generation tasks like text-to-SQL, but is it worth the cost? Many state-of-the-art approaches use non-task-specific LLM t

Citation Failure: Definition, Analysis and Efficient Mitigation

arXiv:2510.20303v3 Announce Type: replace Abstract: Citations from LLM-based RAG systems are supposed to simplify response verification. However, this goal is undermined in cases of citation failure,

Combating Visual Neglect and Semantic Drift in Large Multimodal Models for Enhanced Cross-Modal Retrieval

model-releasesarxiv-cs-cv

arXiv:2604.25273v1 Announce Type: new Abstract: Despite significant progress in Unified Multimodal Retrieval (UMR) powered by Large Multimodal Models (LMMs), existing embedding methods primarily focus

CORAL: Adaptive Retrieval Loop for Culturally-Aligned Multilingual RAG

arXiv:2604.25676v1 Announce Type: new Abstract: Multilingual retrieval-augmented generation (mRAG) is often implemented within a fixed retrieval space, typically via query or document translation or m

safetyarxiv-cs-cl

CoreFlow: Low-Rank Matrix Generative Models

arXiv:2604.24959v1 Announce Type: new Abstract: Learning matrix-valued distributions from high-dimensional and possibly incomplete training data is challenging: ambient-space generative modeling is co

researcharxiv-cs-lg

DCD: Decomposition-based Causal Discovery from Autocorrelated and Non-Stationary Temporal Data

arXiv:2602.01433v2 Announce Type: replace Abstract: Multivariate time series in domains such as finance, climate science, and healthcare often exhibit long-term trends, seasonal patterns, and short-te

applicationsarxiv-cs-lg