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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

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Sparse Graph Learning from Sparse Data via Fiedler Number Maximization

DGX agent

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

30 Apr 2026

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

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

researcharxiv-cs-cl

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

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

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

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

Local 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

model-releasesarxiv-cs-ai

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

model-releasesarxiv-cs-ai

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

model-releasesarxiv-cs-ai

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

researcharxiv-cs-cl

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

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

researcharxiv-cs-cl

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

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

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

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

Text Style Transfer with Machine Translation for Graphic Designs

arXiv:2604.26361v1 Announce Type: cross Abstract: Globalization of graphic designs such as those used in marketing materials and magazines is increasingly important for communication to broad audience

Text-Utilization for Encoder-dominated Speech Recognition Models

arXiv:2604.26514v1 Announce Type: cross Abstract: This paper investigates efficient methods for utilizing text-only data to improve speech recognition, focusing on encoder-dominated models that facili

The Alignment Flywheel: A Governance-Centric Hybrid MAS for Architecture-Agnostic Safety

arXiv:2603.02259v2 Announce Type: replace-cross Abstract: Multi-agent systems provide mature methodologies for role decomposition, coordination, and normative governance, capabilities that remain esse

safetyarxiv-cs-lg

The Bandit's Blind Spot: The Critical Role of User State Representation in Recommender Systems

arXiv:2604.26651v1 Announce Type: cross Abstract: With the increasing availability of online information, recommender systems have become an important tool for many web-based systems. Due to the conti

The devil is in the details: Enhancing Video Virtual Try-On via Keyframe-Driven Details Injection

arXiv:2512.20340v3 Announce Type: replace Abstract: Although diffusion transformer (DiT)-based video virtual try-on (VVT) has made significant progress in synthesizing realistic videos, existing metho

researcharxiv-cs-cv

The Dual Role of Abstracting over the Irrelevant in Symbolic Explanations: Cognitive Effort vs. Understanding

arXiv:2602.03467v2 Announce Type: replace Abstract: Explanations are central to human cognition, yet AI systems often produce outputs that are difficult to understand. While symbolic AI offers a trans

The False Resonance: A Critical Examination of Emotion Embedding Similarity for Speech Generation Evaluation

arXiv:2604.26347v1 Announce Type: cross Abstract: Objective metrics for emotional expressiveness are vital for speech generation, particularly in expressive synthesis and voice conversion requiring em

safetyarxiv-cs-cl

The Fools are Certain; the Wise are Doubtful: Exploring LLM Confidence in Code Completion

arXiv:2508.16131v2 Announce Type: replace-cross Abstract: Code completion entails the task of providing missing tokens given a surrounding context. It can boost developer productivity while providing

The hidden risks of temporal resampling in clinical reinforcement learning

arXiv:2602.06603v3 Announce Type: replace Abstract: Reinforcement learning (RL) is a type of artificial intelligence for making optimal choices. In healthcare, researchers generally use offline RL (OR

applicationsarxiv-cs-lg

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences

arXiv:2509.11295v2 Announce Type: replace Abstract: Developing effective prompts demands significant cognitive investment to generate reliable, high-quality responses from Large Language Models (LLMs)

The Serial Scaling Hypothesis

arXiv:2507.12549v4 Announce Type: replace Abstract: While machine learning has advanced through massive parallelization, we identify a critical blind spot: some problems are fundamentally sequential.

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

Theory-Grounded Evaluation Exposes the Authorship Gap in LLM Personalization

arXiv:2604.26460v1 Announce Type: new Abstract: Stylistic personalization - making LLMs write in a specific individual's style, rather than merely adapting to task preferences - lacks evaluation groun