Search: “models”

Rethinking Brain Decoding with CLIP: The Role of Adversarial Robustness

arXiv:2607.03165v1 Announce Type: new Abstract: Brain decoding aims to uncover neural mechanisms by inferring stimulus-related representations from brain signals. In fMRI studies, this is typically ac

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Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective

DGX agent

arXiv:2607.03784v1 Announce Type: cross Abstract: While prior studies have successfully compressed vision Transformers (ViTs) through various pruning techniques, most have concentrated on width prunin

researcharxiv-cs-ai

7 Jul 2026

Rethinking Scientific Discovery in an Agentic Era

arXiv:2607.03863v1 Announce Type: new Abstract: Artificial intelligence has advanced scientific discovery, but most AI4Science systems remain fragmented tools that rely on humans to coordinate problem

agentsarxiv-cs-cl

RL-Ballast: Ship Ballast Water Path Planning and Clog Prediction via Reinforcement Learning

arXiv:2607.04906v1 Announce Type: new Abstract: Under the Shipping 4.0 paradigm, autonomous and reduced-crew vessels require intelligent internal systems to maintain operational safety and structural

safetyarxiv-cs-lg

RUFNet: Query-Guided Support Mask Refinement and Uncertainty Fusion based on Hybrid Mamba for Few-Shot Brain Tumor Segmentation

arXiv:2607.05035v1 Announce Type: cross Abstract: Few-shot brain tumor segmentation remains challenging due to noisy support masks, inter-patient variations between support and query images, and the l

Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control

arXiv:2603.10938v2 Announce Type: replace-cross Abstract: Safe Reinforcement Learning from Human Feedback (RLHF) typically enforces safety through expected cost constraints, but the expectation captur

Saving GPU Hours in LLM Inference System Development and Online Workloads with Simulation and DBMS-Inspired Cache Replacement Policies

arXiv:2411.07447v5 Announce Type: replace-cross Abstract: LLMs are increasingly used world-wide from daily tasks to agentic systems and data analytics, requiring significant GPU resources. While LLM i

Scalable Cross-Attention Transformer for Cooperative Multi-AP OFDM Uplink Reception

arXiv:2602.04728v3 Announce Type: replace-cross Abstract: We propose a cross-attention Transformer for joint decoding of uplink OFDM signals received by multiple coordinated access points. A shared pe

Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes

arXiv:2607.03392v1 Announce Type: cross Abstract: The ever-increasing collection of personal data has created mounting pressure to develop technologies that protect sensitive aspects of individual ide

Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration

arXiv:2606.12913v2 Announce Type: replace-cross Abstract: The rapid growth of modern training datasets has significantly increased computational cost, motivating dataset pruning~(DP) methods which ret

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment

arXiv:2607.03193v1 Announce Type: cross Abstract: Calibrating a superconducting transmon chip is a sequential decision problem under noise, drift, and a finite budget: an expert must choose experiment

agentsarxiv-cs-ai

Self-Supervised Learning from Structural Invariance

arXiv:2602.02381v2 Announce Type: replace Abstract: Joint-embedding self-supervised learning (SSL), the key paradigm for unsupervised representation learning from visual data, learns from invariances

Semantic Homogenization in Italian Popular Music: A Diachronic Analysis

arXiv:2607.04832v1 Announce Type: new Abstract: In recent years, studies have revealed a decline in semantic variety across popular music lyrics, particularly in English-language songs on streaming pl

researcharxiv-cs-cl

Semantic Segmentation-Driven Image-Level Diagnosis of Liver Cancers in Hematoxylin and Eosin Histopathology Images

arXiv:2607.03253v1 Announce Type: cross Abstract: As hematoxylin & eosin (H&E) staining constitutes the primary entry point in routine diagnostic workflows, computer-aided diagnosis from whole-slide H

SGF-CDNet: A Consistency-Discrepancy Graph Network over Semantic-Geometric Fused Nodes for Face Forgery Detection

arXiv:2607.03883v1 Announce Type: new Abstract: The rapid advancement of deepfakes necessitates robust face forgery detection. Although forged faces may lack obvious artifacts, they often contain subt

SHiPPO: Recurrent Memory with Transported Polynomial Projections

arXiv:2607.03055v1 Announce Type: new Abstract: HiPPO gives recurrent states memory semantics as coefficients of online polynomial projections, but in fixed channel coordinates. Modern selective SSMs,

Applications

Signal from Space: Detecting Schools and Towers to Bridge the Digital Divide

arXiv:2607.02724v1 Announce Type: cross Abstract: Reliable internet access is essential for modern education, yet millions of school-aged children especially in developing regions remain offline due t

applicationsarxiv-cs-ai

SkillFab: An Agent-Native Skill Production Platform

arXiv:2607.03780v1 Announce Type: cross Abstract: SkillFab is an agent-native platform for turning missing capabilities into reviewed, reusable Agent Skills. At runtime, agents first search for reusab

agentsarxiv-cs-ai

SparseOcc++: Geometry-Aware Sparse Latent Representation for Semantic Occupancy Prediction

arXiv:2607.04732v1 Announce Type: new Abstract: Vision-based 3D semantic occupancy prediction is essential for autonomous driving, yet dense voxel representations waste computation on largely empty sp

agentsarxiv-cs-cv

Spectral Gradient Descent Mitigates Anisotropy-Driven Misalignment: A Case Study in Phase Retrieval

arXiv:2601.22652v2 Announce Type: replace-cross Abstract: Spectral gradient methods, such as the Muon optimizer, modify gradient updates by preserving directional information while discarding scale, a

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SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery

arXiv:2602.17395v2 Announce Type: replace-cross Abstract: Generalized Category Discovery (GCD) aims to identify novel categories in unlabeled data while leveraging a small labeled subset of known clas

STAC: Selective Spatiotemporal Aggregation and Compression for Video Reasoning Segmentation

arXiv:2607.02922v1 Announce Type: new Abstract: Video reasoning segmentation demands pixel-accurate object tracking across hundreds of frames under complex natural language queries, producing dense sp

Applications

Steering Optimisation Trajectories in Diffusion Representation Learning

arXiv:2607.05319v1 Announce Type: cross Abstract: We study why diffusion autoencoders can achieve similar image quality while learning substantially different latent structures. We trace this behaviou

applicationsarxiv-cs-ai

Streaming Neural Speech Codecs through Time-Invariant Representations

arXiv:2607.05250v1 Announce Type: new Abstract: Neural speech codecs are increasingly used as intermediate representations in codec-based speech generation systems. TiCodec introduces a factorized rep

researcharxiv-cs-cl

SurgAM: Surgical Affordance Map Prediction with Multimodal Feature Fusion for Robot Autonomy

arXiv:2607.04378v1 Announce Type: new Abstract: Surgical automation is being increasingly studied, yet bridging visual scene understanding with autonomous action planning remains a fundamental challen

agentsarxiv-cs-ro

SWIFT: Spatio-temporal Wavelet Integrated Forecasting Framework for Workload Traces

arXiv:2607.02524v1 Announce Type: cross Abstract: Accurate cloud workload forecasting is pivotal for efficient resource management but remains challenging as workloads are highly volatile and prone to

SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion

arXiv:2607.05392v1 Announce Type: new Abstract: We present SynCity 3000, a framework for generating 3D scenes that are globally coherent while enabling fine-grained layout control. Building on the abi

TAMA: A Human-AI Collaborative Thematic Analysis Framework Using Multi-Agent LLMs for Clinical Interviews

arXiv:2503.20666v2 Announce Type: replace-cross Abstract: Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable in

agentsarxiv-cs-cl

Text as Partial Constraint: Core-Residual Alignment for Robust Vision-Language Learning

arXiv:2607.03143v1 Announce Type: cross Abstract: Vision-language alignment powers open-vocabulary recognition, retrieval, and LVLM grounding, yet natural captions are often underspecified, making sim

Text Dictates, Music Decorates: Energy-based Attention for Editable Dance Motion Generation

arXiv:2606.22726v2 Announce Type: replace Abstract: Choreographic motion generation poses unique challenges for AI, demanding precise semantic control over complex, temporally structured, and expressi

ThreatVisionAI: A Hybrid CNN-ViT Framework for Image-Based Malware Classification

arXiv:2607.03653v1 Announce Type: cross Abstract: Traditional malware detection methods struggle to generalize to obfuscated or previously unseen threats. This paper introduces ThreatVisionAI, a hybri

TokAN: Accent Normalization Using Self-Supervised Speech Tokens

arXiv:2607.03928v1 Announce Type: cross Abstract: Accent normalization (AN) seeks to convert non-native (L2) accented speech into standard (L1) speech while preserving speaker identity. The current te

Toward Efficient Uncertainty in LLMs through Evidential Knowledge Distillation

arXiv:2507.18366v2 Announce Type: replace Abstract: Accurate uncertainty quantification remains a key challenge for standard LLMs, prompting the adoption of Bayesian and ensemble-based methods. Howeve

Toward Personalized Social Robots for Child Well-being: Data Requirement Principles from a Recommender-System Perspective

arXiv:2607.05110v1 Announce Type: cross Abstract: Social robots are increasingly deployed in clinical settings to support the well-being of children, where effective support must be personalized to ea

researcharxiv-cs-ro

Towards Data-Driven Metrics for Social Robot Navigation Benchmarking

arXiv:2509.01251v3 Announce Type: replace Abstract: This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy opt

safetyarxiv-cs-ro

Tracing 3D Anatomy in 2D Strokes: A Multi-Stage Projection Driven Approach to Cervical Spine Fracture Identification

arXiv:2601.15235v4 Announce Type: replace-cross Abstract: Cervical spine fractures require rapid and accurate diagnosis, yet automatic CT interpretation remains challenging as subtle injuries must be

Transformer-Based Multi-Agent Reinforcement Learning for Networked Systems with Long-Range Interactions

arXiv:2511.13103v2 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) has shown promise for large-scale network control, yet existing methods face two major limitations. First,

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TRISTAR: Triple-Signal Stair Recognition and Vision-Only Indoor Navigation for Search-and-Rescue Micro-UAVs

arXiv:2607.03818v1 Announce Type: new Abstract: Indoor search-and-rescue (SAR) operations often require rapid situational awareness where GNSS signals are unavailable and human access is difficult or

agentsarxiv-cs-cv

Understanding electricity consumption behaviour through Inverse Reinforcement Learning

arXiv:2607.03176v1 Announce Type: new Abstract: Understanding how households consume electricity in response to socioeconomic and climatic drivers is important for decision-makers designing energy pol

UniSpine-GS: An Efficient Physics-Aware Gaussian Framework for Cross-Modality Multi-view Spine Image Synthesis

arXiv:2607.04923v1 Announce Type: new Abstract: The diagnosis of spinal diseases is often assisted by 3D imaging techniques in clinical practice. However, precise 3D spinal assessment is limited by th

Untrusted Content Masking for Web Agents with Security Guarantees

arXiv:2607.05277v1 Announce Type: cross Abstract: Defenses that provide security guarantees against prompt injection attacks rely on strict isolation between trusted instructions and untrusted data. I

agentsarxiv-cs-lg

Validation-Induced Shapley Shifts: How Validation Structure Distorts Data Valuation

arXiv:2607.03675v1 Announce Type: new Abstract: Shapley values are widely used to attribute value to training data based on their marginal contribution to performance on a validation set. Existing pra

Applications

What is Left for Us? Second Scholarship Against the Degradation of Research by AI

arXiv:2607.04049v1 Announce Type: new Abstract: We argue that generative AI can degrade research by eroding the very practices through which scholarly judgement is formed and academic trust is built.

applicationsarxiv-cs-ai

When Geometry Aligns: Dihedral Hidden-State Transformations in UNet, ViT, and DiT Architectures

arXiv:2607.03580v1 Announce Type: cross Abstract: Diffusion architectures now encompass convolutional UNets as well as transformer-based designs such as Diffusion Transformers (DiTs), inspired by Visi

Local Ai

When Words Predict Workload

arXiv:2607.04951v1 Announce Type: cross Abstract: Standard distributed ac{llm} schedulers rely on static token counts or rolling latency averages, making them susceptible to failures on statutorily co

local-aiarxiv-cs-cl

Why Pure Reasoning is Not Enough: Nature as the Source of Mathematical Innovation

arXiv:2607.04505v1 Announce Type: new Abstract: We advance the hypothesis that human mathematical reasoning, constrained by both the undecidability and the computational intractability of even modest

WorldMesh: Generating Navigable Multi-Room 3D Scenes via Mesh-Conditioned Image Diffusion

arXiv:2603.22972v3 Announce Type: replace Abstract: Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -vi

Local Ai

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection

arXiv:2607.04350v1 Announce Type: new Abstract: Online social media posts provide scalable signals for early depression screening, and recent studies mainly improve pre-classification evidence through

local-aiarxiv-cs-cl