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Semi-Tensor Product-Based Multi-Term Randomized T-SVD and Its Visual Applications

arXiv:2609.11168v1 Announce Type: new Abstract: Tensor singular value decomposition (T-SVD), which is built upon the tensor-tensor product (t-product), has emerged as a powerful tool for processing hi

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Semidefinite Programming for Quantum Channel Learning

DGX agent

arXiv:2601.12502v2 Announce Type: replace Abstract: The problem of reconstructing a quantum channel from a sample of classical data is considered. When the total fidelity can be represented as a ratio

researcharxiv-cs-lg

11 Sept 2026

SenseNova-U1.5: Towards Native Unified Visual Intelligence

arXiv:2609.11929v1 Announce Type: new Abstract: We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free

safetyarxiv-cs-cv

Sequence-Informed Geometric Evaluation of RNA 3D Structures

arXiv:2609.10644v1 Announce Type: cross Abstract: Computational RNA structure pipelines generate many candidate conformations for the same sequence. Reliable evaluation therefore requires more than re

Seven Sources of Physical AI Capability Formation

arXiv:2609.09627v1 Announce Type: new Abstract: Capabilities relevant to Physical AI can arise from materially different formation histories, yet existing taxonomies organized by morphology, architect

researcharxiv-cs-ai

SG-Blend: Learning an Interpolation Between Improved Swish and GELU for Robust Neural Representations

arXiv:2505.23942v2 Announce Type: replace Abstract: Prevailing activation functions such as Swish and GELU tend toward domain-specific optima, Swish was discovered via neural architecture search on vi

SGA: Plug&Play Geometric Verification for Educational Video Synthesis

arXiv:2607.18116v2 Announce Type: replace-cross Abstract: Recent work leverages Large Language Models (LLMs) to generate executable code for pedagogical animations using libraries such as Manim. Howev

Shedding Light: A Benchmark for Evaluating Lighting Understanding in Generative Image Models

arXiv:2609.10787v1 Announce Type: new Abstract: Accurate modelling of illumination is central to realistic image synthesis and scene understanding. Yet, there is little exploration into whether image

Shifting Relational Paradigms for Affective Computing: Affective Resonance, Vitality Affects, and Vocal Interaction Fields

arXiv:2609.09864v1 Announce Type: new Abstract: Affective computing has largely followed an individual-state paradigm, extracting discrete emotion labels or arousal/valence from isolated speakers. We

researcharxiv-cs-ai

Applications

Single Microphone Own Voice Detection based on Simulated Transfer Functions for Hearing Aids

arXiv:2603.02724v2 Announce Type: replace-cross Abstract: This paper presents a simulation-based approach to own voice detection (OVD) in hearing aids using a single microphone. While OVD can signific

applicationsarxiv-cs-lg

Single-Stream Multi-Feature Fusion with Temporal Robustness for Gait Emotion Recognition

arXiv:2609.11680v1 Announce Type: new Abstract: 3D skeleton-based gait emotion recognition faces high annotation costs, data scarcity, and poor generalization on heterogeneous data. This paper propose

SIRF: A Spec-Internalized Risk Foundation Model for Industrial Content Risk Control

arXiv:2609.11752v1 Announce Type: cross Abstract: For industrial content risk control, the real deployment constraint is not average accuracy but how much risk can be auto-handled under high precision

Agents

Smart Adaptive Computing Across the Continuum: LLMs in IoT-Edge-Cloud Resource Management

arXiv:2609.09348v1 Announce Type: cross Abstract: Managing resources across IoT, edge, and cloud layers calls for continuous, context-aware decisions under constraints that rarely stay fixed. Deep rei

agentsarxiv-cs-ai

Smoothing the Score Function to Enhance Generalization in Diffusion Models

arXiv:2601.19285v3 Announce Type: replace Abstract: Diffusion models achieve remarkable generation quality, yet face a fundamental challenge known as memorization, where generated samples can replicat

SoK: Privacy Attacks on Machine Learning via Explainable AI

arXiv:2609.10627v1 Announce Type: cross Abstract: Machine learning explanations reveal model behavior beyond predictions, creating attack surfaces for model confidentiality and data privacy. We system

Solving Few-Shot Multiobjective Multitask Optimization via Iterative Sequential Transfer

arXiv:2609.11228v1 Announce Type: new Abstract: Applying knowledge transfer across multiple optimization tasks, multitask optimization (MTO) emerges as a promising approach to solving synergistic opti

Sparsity Regularized and Robust Mean Variance Portfolio Selection Under Ellipsoidal Uncertainty

arXiv:2609.11749v1 Announce Type: cross Abstract: We investigate mean-variance portfolio selection with an ell_0-penalty to promote sparsity in asset allocations. Uncertainty in the mean return vector

Spec-Harness: Measuring and Improving Behavioral Adequacy of LLM-Synthesized Formal Specifications

model-releasesarxiv-cs-ai

arXiv:2604.00280v2 Announce Type: replace-cross Abstract: Formal specifications play a central role in ensuring software reliability, yet automatically synthesizing high-quality specifications remains

SpecGuard: Inference-Time Backdoor Detection For Free

arXiv:2609.11799v1 Announce Type: cross Abstract: Large language models are often fine-tuned, shared, or downloaded from third parties, so a deployed model may carry a hidden backdoor that behaves nor

Spectral Adapters for Segment Anything Model-based Segmentation of Colorectal Liver Metastases in Computed Tomography

arXiv:2609.11703v1 Announce Type: new Abstract: Accurate segmentation of colorectal liver metastases (CRLM) in contrast-enhanced computed tomography (CT) is important for response assessment, surgical

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation

arXiv:2506.08949v2 Announce Type: replace Abstract: In the era of information explosion, efficiently leveraging large-scale unlabeled data while minimizing the reliance on high-quality pixel-level ann

Statistical analysis of Inverse Entropy-regularized Reinforcement Learning

arXiv:2512.06956v2 Announce Type: replace-cross Abstract: Inverse reinforcement learning aims to infer the reward function that explains expert behavior observed through trajectories of state--action

Story Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble

arXiv:2609.10883v1 Announce Type: cross Abstract: Language models are trained to implement a helpful AI Assistant character (e.g., Claude). We explore how finetuning on synthetic stories affects this

Strategic Type Spaces

arXiv:2606.08297v2 Announce Type: replace-cross Abstract: We provide a strategic foundation for information: in any given game with incomplete information we define strategic quotients as information

Streaming Translation and Transcription Through Speech-to-Text Causal Alignment

arXiv:2603.11578v2 Announce Type: replace Abstract: Simultaneous machine translation (SiMT) has traditionally relied on offline machine translation models coupled with human-engineered heuristics or l

Structural priors for data-efficient language learning

arXiv:2609.11505v1 Announce Type: new Abstract: Efficient language learning requires methods to reduce the reliance on large data and computational resources. We investigate structural transfer: First

Structural Process Supervision for Latent Chain-of-Thought Reasoning

arXiv:2609.09928v1 Announce Type: new Abstract: Latent reasoning approaches enhance token-level efficiency and robustness by replacing verbose, explicit chain-of-thought (CoT) tokens with compact cont

safetyarxiv-cs-ai

Structurally Speaking: Motif-Oriented Graph Captioning through Bidirectional Graph-Text Translation

arXiv:2609.10923v1 Announce Type: new Abstract: Graph captions should help readers understand graph structure, rather than simply translate adjacency matrices into long textual edge lists. A useful gr

Structured Transforms for Low-Overhead Quantization of Language Models

arXiv:2609.11687v1 Announce Type: new Abstract: We revisit Kashin-decomposition-based weight quantization for large language models and propose an improved algorithm with stronger convergence properti

Studying Without a Syllabus: Task-Agnostic Environment Preprocessing

arXiv:2609.10824v1 Announce Type: cross Abstract: Before an LLM agent tackles tasks in a new environment, it can inspect available corpora and tools and construct reusable resources such as indices, s

Subgroup Membership Inference Audits of Differentially Private Synthetic Text

model-releasesarxiv-cs-ai

arXiv:2609.09848v1 Announce Type: cross Abstract: Synthetic data releases are increasingly proposed in the literature as a means of sharing realistic data replicas in lieu of sensitive private dataset

Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters

arXiv:2501.12299v3 Announce Type: replace-cross Abstract: Gaussian Mixture Models (GMMs) range among the most frequently used models in machine learning. However, training large, general GMMs becomes

Tutorials

Supply Chain Analytics: A Data-Driven Approach

arXiv:2609.10563v1 Announce Type: cross Abstract: Modern supply chain networks increasingly rely on real-time data to navigate structural uncertainties, market volatility, and operational disruptions.

tutorialsarxiv-cs-lg

SwarmNxt: Open-source Software-Hardware Platform for Fast and Agile Aerial Swarms

arXiv:2609.11382v1 Announce Type: new Abstract: Aerial robot swarms have the potential to transform time-critical safety, security, and search-and-rescue operations. By coordinating multiple robots, t

safetyarxiv-cs-ro

SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations

arXiv:2609.11414v1 Announce Type: new Abstract: Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing

Symmetry-aware super-resolution of crystal orientation maps via invariant latent-space learning

arXiv:2609.10898v1 Announce Type: new Abstract: Crystal-orientation maps are physical fields defined only up to crystal symmetry; electron backscatter diffraction (EBSD) resolves them experimentally,

SynCo: Synthetic Community-Aware Attributed Graph Generator for Graph Neural Network Benchmarking

arXiv:2609.10742v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are powerful models for handling attributed graphs in tasks such as classification, link prediction, and community detect

T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks

arXiv:2609.11042v1 Announce Type: new Abstract: Agent usage is shifting toward long-horizon tasks such as coding and scientific discovery, among which terminal tasks are especially important. We intro

TailProp: content-adaptive light- and heavy-tailed propagation for vision

arXiv:2609.11081v1 Announce Type: new Abstract: Science-inspired vision models show that explicit propagation dynamics can provide structured and interpretable alternatives to conventional token mixin

Talking to Itself While Coding: What Makes Comments Help Code Generation?

arXiv:2609.09242v1 Announce Type: cross Abstract: Large Language Models (LLMs) often generate natural-language comments while writing code, and these comments become part of the context used to genera

researcharxiv-cs-ai

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

arXiv:2609.11838v1 Announce Type: new Abstract: Cardiovascular screening models trained on national health surveys routinely report areas under the receiver operating characteristic curve (AUROC) near

Applications

TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription

arXiv:2609.11904v1 Announce Type: new Abstract: Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as

applicationsarxiv-cs-lg

Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems

arXiv:2609.10746v1 Announce Type: cross Abstract: The growing reliance on Low-Earth Orbit (LEO) satellite communication systems has increased the need for intelligent methods capable of detecting cybe

Test time training enhances in-context learning of nonlinear functions

arXiv:2509.25741v3 Announce Type: replace-cross Abstract: Test-time training (TTT) enhances model performance by explicitly updating designated parameters prior to each prediction to adapt to the test

Testing Between the Test Cases: Proving End-to-End Steering in Conditions You Never Drove

arXiv:2609.10951v1 Announce Type: cross Abstract: AI-based automated vehicle testing is challenging because a model that passes every test condition can still fail in the real world. Formal verificati

The Eloquence submission for Task 2 of the Interspeech 2026 MLC-SLM challenge

arXiv:2609.11724v1 Announce Type: new Abstract: This paper details the Eloquence team's approach to Task 2 of the 2nd MLC-SLM challenge at Interspeech 2026, which involves multilingual Multiple-Choice

The Era by Eon Benchmark: A Generated Enterprise Estate with Exact Ground Truth for Benchmarking LLM Agents

model-releasesarxiv-cs-ai

arXiv:2609.09853v1 Announce Type: new Abstract: LLM agents for enterprise systems of record cannot be evaluated on customer production data, and no existing substitute provides ground truth. We presen

The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based Methods

arXiv:2609.11247v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) remains constrained by modality imbalance, yet the field continues to rely on optimization-based balancing methods t