Search: “benchmark”

Structural Plan-to-Model Conversion with Deterministic Geometry and Guarded Agentic Vision-Language Refinement

arXiv:2608.17237v1 Announce Type: cross Abstract: Converting structural framing plans into editable finite-element model drafts remains labor-intensive and prone to transcription error. Existing drawi

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Supporting Calibrated Reliance in Human-AI Collaboration: Different Strategies for Different Tasks

DGX agent

arXiv:2604.03237v2 Announce Type: replace-cross Abstract: As AI systems increasingly support human decision making, a central challenge is determining what information helps people recognize when to r

model-releasesarxiv-cs-ai

19 Aug 2026

TabNSM: Neural Sparse Mixer for Tabular Regression

arXiv:2608.18026v1 Announce Type: new Abstract: Large-scale, high-dimensional tabular regression remains challenging: tree-based models are robust but lack end-to-end representation learning, while de

applicationsarxiv-cs-lg

TabularQGAN: A quantum generative model for tabular data synthesis

arXiv:2505.22533v2 Announce Type: replace-cross Abstract: In this paper, we introduce a novel quantum generative model for synthesizing tabular data. Synthetic data is valuable in scenarios where real

applicationsarxiv-cs-ai

TileMix: Tile-Centric Mixed-Precision Attention for LLM Inference Acceleration

arXiv:2608.17336v1 Announce Type: new Abstract: Long-context prefill in large language models (LLMs) incurs substantial computation and memory traffic because dense self-attention computes quadratic q

TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts

arXiv:2602.21693v2 Announce Type: replace Abstract: Multimodal time series forecasting has garnered significant attention for its potential to provide more accurate predictions than traditional single

safetyarxiv-cs-lg

TokEval: A Tokenizer Evaluation Suite

arXiv:2608.18062v1 Announce Type: new Abstract: Language model tokenizers are typically selected with minimal evaluation, despite the fact that their design choices directly impact model capabilities.

safetyarxiv-cs-cl

Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight

arXiv:2510.08713v3 Announce Type: replace Abstract: Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typical

TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation

arXiv:2608.17588v1 Announce Type: new Abstract: Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities with

Uncertainty-Aware Decision Making in Multimodal Large Language Models

arXiv:2608.17084v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) increasingly answer questions whose correctness depends on visual, textual, temporal, acoustic, document, chart

safetyarxiv-cs-cl

Understanding Curriculum Learning in Large Language Models via Cross-Difficulty Optimization Dynamics

arXiv:2608.17268v1 Announce Type: cross Abstract: Curriculum learning has been widely adopted in the post-training of large language models by organizing training data from easy to hard. However, its

Vision Transformers for End-to-End Quark-Gluon Jet Classification from Calorimeter Images

arXiv:2506.14934v2 Announce Type: replace Abstract: Distinguishing between quark- and gluon-initiated jets is a critical and challenging task in high-energy physics, pivotal for improving new physics

researcharxiv-cs-cv

When to Review: Spaced Repetition for Continual Pre-Training of Language Models

arXiv:2608.17530v1 Announce Type: new Abstract: Continual pre-training of large language models must acquire new information without erasing old knowledge. Existing replay methods often choose a globa

Which Source Wins? Task-Dependent Reliance in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2608.17205v1 Announce Type: new Abstract: Vision-language models (VLMs) combine images and text, but when the two conflict and one becomes harder to read, it is unclear how a model shifts its re

A Bi-directional Multi-solution Scalable Grover Search Algorithm

arXiv:2404.15616v2 Announce Type: replace-cross Abstract: Grover's search algorithms, including various Partial Grover Searches (PGS), suffer from scaling issues when multiple solutions are sought, as

A Comprehensive Survey of Wireless Foundation Models for AI-Native 6G Networks

arXiv:2608.14694v1 Announce Type: new Abstract: Foundation models are emerging as a transformative paradigm for AI-native sixth-generation (6G) wireless networks by enabling scalable, transferable, an

A Machine-Learned Comorbidity Index

arXiv:2606.17450v2 Announce Type: replace Abstract: Traditional comorbidity scores (e.g., Charlson and Elixhauser) are widely used for risk adjustment and patient stratification, but they have two key

A Policy Algebra for Trust-Preserving Agentic AI Execution

arXiv:2608.16402v1 Announce Type: new Abstract: Large language model-based agentic frameworks primarily optimize capability: whether an agent can reason, retrieve information, call tools, delegate wor

A Scalable Pipeline for LLM-Teacher Distillation Labeling: Work-Stealing Job Scheduling and Memory-Aware GPU Concurrency

arXiv:2608.15975v1 Announce Type: cross Abstract: Labeling large text corpora with LLM teachers has become a practical route to training data at scale. At millions of items, hand-labeling every batch

A survey of AI-generated voices and their detection

arXiv:2608.15411v1 Announce Type: new Abstract: The ability of artificial intelligence (AI) models to generate highly realistic human voices has advanced rapidly. These technologies power accessibilit

A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems

arXiv:2606.14582v2 Announce Type: replace Abstract: Efficient route optimization play a vital role in ensuring both safety and punctuality in railway operations. It is very crucial particularly in het

A Versatile Foundation Model for AI-enabled Mammogram Interpretation

model-releasesarxiv-cs-cv

arXiv:2509.20271v2 Announce Type: replace Abstract: Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in women globally. Mammography is essential fo

ACTS-SQL: Agentic and Critic-Oriented Tree-Structured SQL Correctness with Large Language Models

arXiv:2608.15145v1 Announce Type: new Abstract: Large Language Models (LLMs) have been increasingly adopted in Text-to-SQL systems, yet SQL errors remain a major obstacle in real-world Text-to-SQL inf

Local Ai

Adapting LLMs to Time Series Forecasting via Temporal Heterogeneity Modeling and Representation Alignment

arXiv:2508.07195v2 Announce Type: replace-cross Abstract: Recent advances have demonstrated that Large Language Models (LLMs) can be effectively adapted for time series forecasting, revealing strong p

local-aiarxiv-cs-ai

Adding Voice Cloning to Text-to-Audio-Video Models with a Single Zero-Initialised Layer

arXiv:2608.15690v1 Announce Type: cross Abstract: Text-to-audio-video (T2AV) generation models produce a video and its soundtrack from a textual description, but offer no control over whose voice spea

AdROD: HyperNetwork-based Adversarially Robust Object Detection for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2608.16031v1 Announce Type: cross Abstract: Camera-based object detectors are vulnerable to physical adversarial attacks designed to suppress detections. While adversarial training and input pur

Advancing Open and Reproducible Relational Learning: RelArena-alpha, TabPFN-Rel and RPI

arXiv:2608.16319v1 Announce Type: new Abstract: This first release of Prior Labs in relational learning shows our continued commitment to open science. We open-source three pieces of software that we

applicationsarxiv-cs-lg

Agents

Agent-Native Telemetry: Verifiable State-Delta Evidence for Autonomous Operations

arXiv:2608.16178v1 Announce Type: cross Abstract: Operational telemetry is predominantly engineered for human reading: systems repeatedly serialize verbose prose, static keys, and redundant context ac

agentsarxiv-cs-ai

Hardware

Algorithm-Architecture Co-Design for Efficient VLA Inference via Speculative Inference and Verification

arXiv:2608.15636v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in the field of embodied AI, but their high computational cost and limit

hardwarearxiv-cs-ai

ALPS: Measuring Valid Creativity in Large Language Models with Mathematical Construction

arXiv:2608.15979v1 Announce Type: new Abstract: Large language models produce outputs presented as discoveries - new proofs, conjectures, or molecules. Whether such an output that appears creative is

Amortised Post-Hoc Explanation with Exact Preservation for Dynamic Graph Anomaly Detectors

arXiv:2608.15559v1 Announce Type: cross Abstract: Anomaly detection in dynamic graphs underpins financial fraud analysis, intrusion detection, and platform integrity, where automated decisions require

Anchor-Regularized Adaptation for Generalizable AI-Generated Image Detection with DINOv3

arXiv:2608.15196v1 Announce Type: new Abstract: Recent works in AI-generated image detection have shown that careful training data alignment can improve generalization by removing spurious correlation

safetyarxiv-cs-cv

ARGUS: Attention-Guided Transformers for Scalable Person Identification Using Wi-Fi Telemetry

arXiv:2608.14670v1 Announce Type: cross Abstract: Passive, device-free person identification offers an alternative to camera- and wearable-based biometrics, yet existing wireless approaches rely large

Assessing LLMs' mathematical abilities requires understanding the various mechanisms of mathematical creativity

arXiv:2608.16118v1 Announce Type: new Abstract: How should we assess whether large language models can perform mathematical invention? I argue that this question is currently underspecified: mathemati

applicationsarxiv-cs-ai

AstronOS: A Unified Execution Model and Runtime for Long-Horizon Agentic Systems

arXiv:2608.16381v1 Announce Type: new Abstract: Agentic systems often organize execution and state around a single conversation, model invocation, or agent instance, even when real work spans many cal

AudioTQ: A Data-Oblivious 6-Bit CPU Audio Codec via Randomized Hadamard Rotation and Lloyd-Max Quantization

arXiv:2608.15369v1 Announce Type: cross Abstract: Lossy audio compression algorithms traditionally rely on psychoacoustic modeling and frequency-domain representations (e.g., MP3, AAC, and Opus) to di

Local Ai

Automatic Cephalometric Landmark Localization on CBCT-Derived Digitally Reconstructed Radiographs for Skeletal Malocclusion Classification

arXiv:2608.16535v1 Announce Type: new Abstract: Manual cephalometric landmark annotation is important for craniofacial assessment but is labor-intensive and difficult to scale. We introduce CephViT, a

local-aiarxiv-cs-cv

AutoMem: A Text-Gradient Recursive Self-Improvement Framework for Automated Memory Architectures Search

arXiv:2608.14621v1 Announce Type: cross Abstract: Long-term memory is increasingly central to LLM agents, yet memory design remains a highly coupled architecture problem: what to encode, how to store

AutoSR: Automatic Symbolic Regression by Searching Research States

arXiv:2608.16876v1 Announce Type: cross Abstract: We introduce Automatic Symbolic Regression (AutoSR), a fully automated system that instantiates Research-Space Symbolic Regression by searching persis

Balancing Optimality and Diversity: Human-Centered Decision Making through Generative Curation

arXiv:2409.11535v3 Announce Type: replace Abstract: Many decision-support systems recommend actions by optimizing measurable objectives, even when a human decision-maker retains final authority and co

safetyarxiv-cs-lg

BERTopic-Virality Prioritisation: A Scalable Framework for Thematic and Comparative Analysis of COVID-19 and Monkeypox Misinformation on Twitter

model-releasesarxiv-cs-cl

arXiv:2608.15691v1 Announce Type: new Abstract: Health misinformation circulating during pandemics can gain traction rapidly, creating harmful narratives that compete with public health guidance. Most

Beyond Correctness: Toward Automated Novelty Verification with Lean 4

arXiv:2608.14669v1 Announce Type: new Abstract: Artificial intelligence systems applied to mathematics verify correctness but not novelty: an automatically generated theorem can compile in Lean withou

Tutorials

Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering

arXiv:2608.15757v1 Announce Type: new Abstract: Incomplete multi-view clustering (IMVC) aims to uncover shared cluster structures from data with partially observed views. Although recent imputation-fr

tutorialsarxiv-cs-cv

Beyond Similarity Matching: Structured Reasoning for Open-Vocabulary Referring Segmentation in 3DGS

arXiv:2608.16103v1 Announce Type: new Abstract: Open-vocabulary referring segmentation in 3D Gaussian Splatting (3DGS) requires a neural model to select Gaussian primitives according to free-form lang

safetyarxiv-cs-cv

Local Ai

Beyond Single Object: Learning 3D Relations with Large Language Models

arXiv:2608.15710v1 Announce Type: cross Abstract: We address a fundamental gap in 3D-LLMs: existing models focus on single-object/scene description, struggling with detailed, inter-object comparison.

local-aiarxiv-cs-ai

Beyond Thresholds: A Quality-Aware Decision Intelligence Framework for Cold Chain IoT Systems

arXiv:2608.15082v1 Announce Type: new Abstract: Cold chain logistics has advanced technologically, yet most deployed systems remain reactive monitors, not decision-making agents: thresholds trigger al

Bitstream Action Recognition is Byte Modeling

model-releasesarxiv-cs-cv

arXiv:2608.15695v1 Announce Type: new Abstract: Conventional action recognition typically relies on successful pixel decoding of the bitstream. However, bitstream corruption during storage or transmis

Bringing Generative Learning to Representation Learning: Self-Supervised Transfer Learning as Distribution Matching

arXiv:2502.14424v3 Announce Type: replace-cross Abstract: Most self-supervised learning objectives defend against collapse but leave the target representation law unspecified. We formulate representat