Search: “model-releases”

Sustainability via LLM Right-sizing

arXiv:2504.13217v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have become increasingly embedded in organizational workflows. This has raised concerns over their energy consump

SVFSearch: A Multimodal Knowledge-Intensive Benchmark for Short-Video Frame Search in the Gaming Vertical Domain

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DGX agent

arXiv:2605.17946v1 Announce Type: new Abstract: Multimodal large language models are increasingly used as agent backbones that understand multimodal inputs, plan retrieval actions, invoke external too

model-releasesarxiv-cs-ai

19 May 2026

SwordBench: Evaluating Orthogonality of Steering Image Representations

arXiv:2605.16372v1 Announce Type: cross Abstract: Steering or intervening on model representations at inference time to correct predictions is essential for AI interpretability and safety, yet existin

Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers

arXiv:2605.18106v1 Announce Type: cross Abstract: A striking geometric disparity has long persisted in the practice of deep learning. While modern neural network architectures naturally exhibit rich s

Symphony for Speech-to-Text: Supporting Real-Time Medical Voice Interfaces

arXiv:2605.16545v1 Announce Type: cross Abstract: After decades of use in dictation and, more recently, ambient documentation, speech is emerging as a primary modality for interacting with technology

TabH2O: A Unified Foundation Model for Tabular Prediction

arXiv:2605.18383v1 Announce Type: new Abstract: We present TabH2O, a foundation model for tabular data that performs classification and regression in a single forward pass via in-context learning. Tab

Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigms

arXiv:2605.17336v1 Announce Type: cross Abstract: Tactile sensing is a fundamental modality for embodied intelligence, offering unique and direct feedback on contact geometry, material properties, and

TailedTS: Benchmark Dataset for Heavy-Tailed Time Series Prediction and Periodicity Quantification

arXiv:2605.16361v1 Announce Type: cross Abstract: We present TailedTS, a large-scale benchmark dataset derived from Wikipedia hourly page view observations throughout 2024, specifically designed to te

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models

arXiv:2605.17577v1 Announce Type: new Abstract: Large-scale pre-trained Vision-Language models (VLMs), such as CLIP, exhibit strong zero-shot generalization, yet remain highly vulnerable to impercepti

Task Abstention for Large Language Models in Code Generation

arXiv:2605.17029v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized automated code generation. One serious concern, however, is the so-called ``hallucination'', i.e., LL

TaskGround: Structured Executable Task Inference for Full-Scene Household Reasoning

arXiv:2605.18109v1 Announce Type: new Abstract: In real home deployments, household agents must often operate from a complete household scene and a situated household request, rather than from a clean

Taxonomy and Consistency Analysis of Safety Benchmarks for AI Agents

arXiv:2605.16282v1 Announce Type: cross Abstract: The rapid deployment of LLM-based autonomous agents has introduced safety risks that extend far beyond traditional LLM concerns, prompting a prolifera

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications?

arXiv:2605.18025v1 Announce Type: new Abstract: While Large Language Models have achieved remarkable integration in various vertical scenarios, their deployment in the telecommunications domain remain

Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations

arXiv:2605.17639v1 Announce Type: new Abstract: Co-citation structure is widely assumed to provide stable retrieval signal in legal information systems. We test this assumption longitudinally by const

Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction

arXiv:2605.16891v1 Announce Type: new Abstract: We introduce a tensor-channel equivariant graph neural network for direct prediction of molecular polarizability tensors. Building on the efficient PaiN

Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation

arXiv:2605.18430v1 Announce Type: new Abstract: Text-to-CAD generation aims to create parametric CAD models from natural language, enabling rapid prototyping and intuitive design workflows. However, e

The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought

arXiv:2605.18079v1 Announce Type: cross Abstract: Existing expressivity results for transformers typically rely on hardmax attention, high precision, and other architectural modifications that disconn

The Illusion of Specialization: Unveiling the Domain-Invariant 'Standing Committee' in Mixture-of-Experts Models

arXiv:2601.03425v2 Announce Type: replace-cross Abstract: Mixture of Experts models are widely assumed to achieve domain specialization through sparse routing. In this work, we question this assumptio

The MixCount Dataset: Bridging the Data Gap for Open-Vocabulary Object Counting

arXiv:2605.18063v1 Announce Type: new Abstract: Object counting is a foundational vision task with over a decade of dedicated research, yet state-of-the-art models still fail systematically in the mix

The Neural Tangent Kernel for Classification

arXiv:2605.17606v1 Announce Type: new Abstract: In wide neural networks, the Neural Tangent Kernel (NTK) remains approximately constant during training, providing a powerful theoretical tool for study

The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning

arXiv:2309.01243v4 Announce Type: replace-cross Abstract: We investigate the privacy of {em any} algorithm whose outputs have Gaussian distribution. This work is motivated by the prevalence of such al

The Powers of Precision: Structure-Informed Detection in Complex Systems -- From Customer Churn to Seizure Onset

arXiv:2601.21170v3 Announce Type: replace Abstract: Emergent phenomena -- onset of epileptic seizures, sudden customer churn, or pandemic outbreaks -- often arise from hidden causal interactions in co

The Range Shrinks, the Threat Remains: Re-evaluating LLM Package Hallucinations on the 2026 Frontier-Model Cohort

arXiv:2605.17062v1 Announce Type: cross Abstract: Spracklen et al. (USENIX Security '25) showed that code-generating large language models hallucinate package names that do not exist on PyPI or npm at

The Scaling Laws of Skills in LLM Agent Systems

arXiv:2605.16508v1 Announce Type: cross Abstract: As agent systems scale, skills accumulate into large reusable libraries, yet their scaling laws remain poorly understood. Across 15 frontier LLMs, 1,1

The Symmetries of Three-Layer ReLU Networks

arXiv:2605.18319v1 Announce Type: new Abstract: We develop a framework for analyzing parameter symmetries in deep ReLU networks and obtain a complete characterization of the generic parameter fibers f

'The Whole Is Greater Than the Sum of Its Parts': A Compatibility-Aware Multi-Teacher CoT Distillation Framework

arXiv:2601.13992v2 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) reasoning empowers Large Language Models (LLMs) with remarkable capabilities but typically requires prohibitive paramet

Theory of Minimal Weight Perturbations in Deep Networks and its Applications for Low-Rank Activated Backdoor Attacks

arXiv:2601.16880v2 Announce Type: replace Abstract: The minimal norm weight perturbations of DNNs required to achieve a specified change in output are derived and the factors determining its size are

Threats to Arabic Handwriting Recognition: Investigating Black-Box Adversarial Attacks on embedded ConvNet models

arXiv:2605.18058v1 Announce Type: new Abstract: Arabic handwriting recognition (AHR) has made significant progress with deep learning models. AHR research has largely focused on performance, with secu

TIER: Trajectory-Invariant Execution Rewards for Multi-Step Tool Composition

arXiv:2605.16790v1 Announce Type: cross Abstract: Tool use enables large language models to solve complex tasks through sequences of API calls, yet existing reinforcement learning approaches fail to s

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval

arXiv:2605.18434v1 Announce Type: cross Abstract: E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This im

Time-Efficient Hybrid Hyperparameter Tuning Approach for Cardiovascular Disease Classification

arXiv:2411.18234v2 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are any serious illness of the heart, which require accurate diagnosis to prevent fatal consequences. Hyperpara

Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis

arXiv:2602.24238v2 Announce Type: replace Abstract: Accurate forecasting of transportation dynamics is essential for urban mobility and infrastructure planning. Although recent work has achieved stron

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model

arXiv:2605.18013v1 Announce Type: cross Abstract: Segment Anything Model 2 (SAM 2) serves as a core foundation model in the field of video segmentation. Building upon the original SAM model, it introd

TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents

arXiv:2605.16909v1 Announce Type: new Abstract: Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate

ToolMATH: A Diagnostic Benchmark for Long-Horizon Tool Use under Systematic Tool-Catalog Constraints

arXiv:2602.21265v2 Announce Type: replace Abstract: We introduce ToolMATH, a math-grounded diagnostic benchmark for evaluating long-horizon tool use under controllable tool-catalog conditions. ToolMAT

Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning

model-releasesarxiv-cs-ro

arXiv:2602.10503v2 Announce Type: replace Abstract: Pretrained on large-scale and diverse datasets, VLA models demonstrate strong generalization and adaptability as general-purpose robotic policies. H

TPV: Parameter Perturbations Through the Lens of Test Prediction Variance

arXiv:2512.11089v4 Announce Type: replace-cross Abstract: We introduce test prediction variance (TPV)--the first-order sensitivity of a trained model's outputs to parameter perturbations--as a unifyin

Transitivity Meets Cyclicity: Explicit Preference Decomposition for Dynamic Large Language Model Alignment

arXiv:2605.17342v1 Announce Type: cross Abstract: Standard RLHF relies on transitive scalar rewards, failing to capture the cyclic nature of human preferences. While some approaches like the General P

TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT

arXiv:2605.16572v1 Announce Type: new Abstract: Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly i

Trust No Tool: Evaluating and Defending LLM Agents under Untrusted Tool Feedback

arXiv:2605.17453v1 Announce Type: cross Abstract: Tool-using LLM agents increasingly rely on external tools to make consequential decisions, yet most existing agent-security benchmarks and defenses im

Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

arXiv:2409.10102v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has quickly grown into a pivotal paradigm in the development of Large Language Models (LLMs). Although ex

TTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens

arXiv:2605.16638v1 Announce Type: new Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this paradig

TusoAI: Agentic Optimization for Scientific Methods

arXiv:2509.23986v2 Announce Type: replace Abstract: Scientific discovery is often slowed by the manual development of computational tools needed to analyze complex experimental data. Building such too

UAVFF3D: A Geometry-Aware Benchmark for Feed-Forward UAV 3D Reconstruction

arXiv:2605.17942v1 Announce Type: new Abstract: Feed-forward 3D reconstruction has recently demonstrated strong generalization across diverse scenes, yet its performance in UAV imagery remains underex

UbuntuGuard: A Culturally-Grounded Policy Benchmark for Equitable AI Safety in African Languages

arXiv:2601.12696v2 Announce Type: replace Abstract: Current guardian models are predominantly Western-centric and optimized for high-resource languages, leaving low-resource African languages vulnerab

UCSF-PDGM-VQA: Visual Question Answering dataset for brain tumor MRI interpretation

arXiv:2605.17140v1 Announce Type: cross Abstract: Brain tumor diagnosis is largely dependent on Magnetic Resonance Imaging (MRI) evaluation, which requires radiologists to synthesize thousands of imag

UniER: A Unified Benchmark for Item-level and Path-level Exercise Recommendation

arXiv:2605.16750v1 Announce Type: cross Abstract: Personalized exercise recommendation dynamically aligns pedagogical resources with individual knowledge mastery, which is crucial for satisfying stude

UniPPTBench: A Unified Benchmark for Presentation Generation Across Diverse Input Settings

arXiv:2605.17356v1 Announce Type: new Abstract: Existing works typically focus on presentation generation under isolated input settings, whereas real-world use cases span diverse scenarios, including