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SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization

arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat

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Seeking Consensus: Geometric-Semantic On-the-Fly Recalibration for Open-Vocabulary Remote Sensing Semantic Segmentation

DGX agent

arXiv:2604.26221v1 Announce Type: cross Abstract: Open-vocabulary semantic segmentation (OVSS) in remote sensing images is a promising task that employs textual descriptions for identifying undefined

safetyarxiv-cs-ai

30 Apr 2026

Select to Think: Unlocking SLM Potential with Local Sufficiency

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

local-aiarxiv-cs-cl

Self-Jailbreaking: Language Models Can Reason Themselves Out of Safety Alignment After Benign Reasoning Training

arXiv:2510.20956v2 Announce Type: replace-cross Abstract: We discover a novel and surprising phenomenon of unintentional misalignment in reasoning language models (RLMs), which we call self-jailbreaki

Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery

arXiv:2502.14912v2 Announce Type: replace Abstract: We present a framework for generating universal semantic embeddings of chemical elements to advance materials inference and discovery. This framewor

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition

arXiv:2604.26262v1 Announce Type: new Abstract: Modern scene reconstruction methods, such as 3D Gaussian Splatting, enable photo-realistic novel view synthesis at real-time speeds. However, their adop

Semi-supervised learning with max-margin graph cuts

arXiv:2604.26818v1 Announce Type: new Abstract: This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels

SG-UniBuc-NLP at SemEval-2026 Task 6: Multi-Head RoBERTa with Chunking for Long-Context Evasion Detection

arXiv:2604.26375v1 Announce Type: cross Abstract: We describe our system for SemEval-2026 Task 6 (CLARITY: Unmasking Political Question Evasions), which classifies English political interview response

researcharxiv-cs-ai

Shorthand for Thought: Compressing LLM Reasoning via Entropy-Guided Supertokens

arXiv:2604.26355v1 Announce Type: new Abstract: Reasoning in Large Language Models incurs significant inference-time compute, yet the token-level information structure of reasoning traces remains unde

Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection

arXiv:2604.26057v1 Announce Type: cross Abstract: Supervised contrastive learning (SupCon) is widely used to shape representations, but has seen limited targeted study for audio deepfake detection. Ex

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

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

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

Sociodemographic Biases in Educational Counselling by Large Language Models

arXiv:2604.25932v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into educational settings, understanding their potential biases is critical. This study ex

safetyarxiv-cs-ai

SongBench: A Fine-Grained Multi-Aspect Benchmark for Song Quality Assessment

arXiv:2604.25937v1 Announce Type: cross Abstract: Recent advancements in Text-to-Song generation have enabled realistic musical content production, yet existing evaluation benchmarks lack the professi

Source-Free Bistable Fluidic Gripper for Size-Selective and Stiffness-Adaptive Grasping

arXiv:2511.03691v2 Announce Type: replace Abstract: Conventional fluid-driven soft grippers typically depend on external sources, which limit portability and long-term autonomy. This work introduces a

researcharxiv-cs-ro

Tutorials

Sparse Graph Learning from Sparse Data via Fiedler Number Maximization

arXiv:2604.26132v1 Announce Type: cross Abstract: We aim to learn a sparse and connected graph from sparse data, where the number of observations K can be substantially smaller than the signal dimensi

tutorialsarxiv-cs-lg

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

Spatially-constrained clustering of geospatial features for heat vulnerability assessment of favelas in Rio de Janeiro

arXiv:2604.26133v1 Announce Type: new Abstract: Informal settlements face disproportionate exposure to climate-related health hazards. However, existing methodologies lack systematic approaches to lin

SpecTr-GBV: Multi-Draft Block Verification Accelerating Speculative Decoding

arXiv:2604.25925v1 Announce Type: new Abstract: Autoregressive language models suffer from high inference latency due to their sequential decoding nature. Speculative decoding (SD) mitigates this by e

Tutorials

Speech Emotion Recognition Using MFCC Features and LSTM-Based Deep Learning Model

arXiv:2604.25938v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) is the use of machines to detect the emotional state of humans based on the speech, which is gaining importance in na

tutorialsarxiv-cs-ai

Split over n resource sharing problem: Are fewer capable agents better than many simpler ones?

arXiv:2604.26374v1 Announce Type: new Abstract: In multi-agent systems, should limited resources be concentrated into a few capable agents or distributed among many simpler ones? This work formulates

agentsarxiv-cs-ro

Applications

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

Applications

STAR-Filter: Efficient Convex Free-Space Approximation via Starshaped Set Filtering in Noisy Environments

arXiv:2604.26626v1 Announce Type: new Abstract: Approximating collision-free space is fundamental to robot planning in complex environments. Convex geometric representations, such as polytopes and ell

applicationsarxiv-cs-ro

Star-Fusion: A Multi-modal Transformer Architecture for Discrete Celestial Orientation via Spherical Topology

arXiv:2604.26582v1 Announce Type: cross Abstract: Reliable celestial attitude determination is a critical requirement for autonomous spacecraft navigation, yet traditional 'Lost-in-Space' (LIS) algori

agentsarxiv-cs-ai

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

STARRY: Spatial-Temporal Action-Centric World Modeling for Robotic Manipulation

arXiv:2604.26848v1 Announce Type: new Abstract: Robotic manipulation critically requires reasoning about future spatial-temporal interactions, yet existing VLA policies and world-model-enhanced polici

safetyarxiv-cs-ro

State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading

model-releasesarxiv-cs-cv

arXiv:2604.26614v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved impressive progress on general multimodal tasks, yet they remain brittle on dial-based measuremen

Applications

STLGT: A Scalable Trace-Based Linear Graph Transformer for Tail Latency Prediction in Microservices

arXiv:2604.26422v1 Announce Type: cross Abstract: Accurate end-to-end tail-latency forecasting is critical for proactive SLO management in microservice systems. However, modeling long-range dependency

applicationsarxiv-cs-ai

Stochastic Entanglement of Deterministic Origami Tentacles For Universal Robotic Gripping

arXiv:2604.26897v1 Announce Type: new Abstract: Origami-inspired robotic grippers have shown promising potential for object manipulation tasks due to their compact volume and mechanical flexibility. H

local-aiarxiv-cs-ro

Stochastic Scaling Limits and Synchronization by Noise in Deep Transformer Models

arXiv:2604.26898v1 Announce Type: cross Abstract: We prove pathwise convergence of the layerwise evolution of tokens in a finite-depth, finite-width transformer model with MultiLayer Perceptron (MLP)

StratMem-Bench: Evaluating Strategic Memory Use in Virtual Character Conversation Beyond Factual Recall

arXiv:2604.26243v1 Announce Type: cross Abstract: Achieving realistic human-like conversation for virtual characters requires not only a simple memorization and recall of past events, but also the str

StreamAgent: Towards Anticipatory Agents for Streaming Video Understanding

arXiv:2508.01875v4 Announce Type: replace Abstract: Real-time streaming video understanding in domains such as autonomous driving and intelligent surveillance poses challenges beyond conventional offl

agentsarxiv-cs-cv

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

Structured and Abstractive Reasoning on Multi-modal Relational Knowledge Images

arXiv:2510.21828v2 Announce Type: replace-cross Abstract: Understanding and reasoning with abstractive information from the visual modality presents significant challenges for current multi-modal larg

Student Guides Teacher: Weak-to-Strong Inference via Spectral Orthogonal Exploration

arXiv:2601.06160v2 Announce Type: replace Abstract: Large Language Models (LLMs) often suffer from ''Reasoning Collapse'' on challenging mathematical reasoning tasks, where stochastic sampling produce

safetyarxiv-cs-ai

Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition

arXiv:2604.26793v1 Announce Type: new Abstract: Motivated by sensing modalities in modern autonomous systems that involve hardware-constrained spatial sampling over large arrays with limited coherence

agentsarxiv-cs-lg

SWAN: World-Aware Adaptive Multimodal Networks for Runtime Variations

arXiv:2604.26181v1 Announce Type: new Abstract: Multimodal deep neural networks deployed in realistic environments must contend with runtime variations: changes in modality quality, overall input comp

agentsarxiv-cs-lg

Swap distance minimization shapes the order of subject, object and verb in languages of the world

arXiv:2604.26726v1 Announce Type: new Abstract: Languages of the world vary concerning the order of subject, object and verb. The most frequent dominant orders are SOV and SVO, and researchers have ta

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

SynSur: An end-to-end generative pipeline for synthetic industrial surface defect generation and detection

arXiv:2604.26633v1 Announce Type: cross Abstract: The bottleneck in learning-based industrial defect detection is often limited not by model capacity, but by the scarcity of labeled defect data: defec

researcharxiv-cs-ai

Talent or Luck? Evaluating Attribution Bias in Large Language Models

arXiv:2505.22910v2 Announce Type: replace Abstract: When a student fails an exam, do we tend to blame their effort or the test's difficulty? Attribution, defined as how reasons are assigned to event o

safetyarxiv-cs-cl

TAP into the Patch Tokens: Leveraging Vision Foundation Model Features for AI-Generated Image Detection

model-releasesarxiv-cs-cv

arXiv:2604.26772v1 Announce Type: new Abstract: Recent methods demonstrate that large-scale pretrained models, such as CLIP vision transformers, effectively detect AI-generated images (AIGIs) from uns

Tatemae: Detecting Alignment Faking via Tool Selection in LLMs

arXiv:2604.26511v1 Announce Type: cross Abstract: Alignment faking (AF) occurs when an LLM strategically complies with training objectives to avoid value modification, reverting to prior preferences o

safetyarxiv-cs-ai

TDD Governance for Multi-Agent Code Generation via Prompt Engineering

arXiv:2604.26615v1 Announce Type: cross Abstract: Large language models (LLMs) accelerate software development but often exhibit instability, non-determinism, and weak adherence to development discipl

agentsarxiv-cs-ai

Teaching LLM to be Persuasive: Reward-Enhanced Policy Optimization for Alignment from Heterogeneous Rewards

arXiv:2510.04214v3 Announce Type: replace Abstract: We deploy large language models (LLMs) as business development (BD) agents for persuasive price negotiation in online travel agencies (OTAs). The ag

safetyarxiv-cs-cl

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