research

Unifying Decision-Making and Trajectory-Planning in Unsignalized Intersections Using Time-Varying Potential Fields

arXiv:2607.13626v1 Announce Type: cross Abstract: This paper presents a novel framework for integrated Decision-Making (DM) and Trajectory Planning (TP) for automated vehicles at unsignalized intersec

Research

UTS at ELOQUENT 2026 Voight-Kampff: structural shifts in AI writing bypass state-of-the-art detectors

DGX agent

arXiv:2607.13565v1 Announce Type: cross Abstract: We investigate which language model evasion attacks survive state-of-the-art adversarial fine-tuning, developing strategies that sweep the top 5 posit

researcharxiv-cs-ai

16 Jul 2026

VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling

arXiv:2607.13929v1 Announce Type: new Abstract: Financial observations are continuous, heterogeneous, and noisy, whereas decoder-only next-token models are usually built around discrete symbolic input

Verifying formulas for interventional distributions

arXiv:2607.13883v1 Announce Type: cross Abstract: We formalize verification in causal graphical models: deciding whether a given observational formula identifies a target interventional distribution.

Video to All-in-focus Image Reconstruction Algorithm for Automated Microscopic Urinalysis

arXiv:2607.13601v1 Announce Type: cross Abstract: Microscopic urinalysis is a routine diagnostic test at hospitals. Recent studies have demonstrated the effectiveness of deep learning methods to autom

What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry

arXiv:2607.13046v1 Announce Type: new Abstract: We develop a framework for the information discarded by machine learning models whose inputs carry a Lie group action. Given a representation pi of a Li

When Audio Separation Hurts Zero-Shot ASR: Evaluating SAM-Audio with Whisper on Bengali and English Speech

arXiv:2603.04710v2 Announce Type: replace-cross Abstract: Recent advances in automatic speech recognition (ASR) and speech enhancement have strengthened the common belief that cleaner audio should lea

When is the combined load identifiable from a stress-intensity profile? A coupled forward-inverse study on SIFBench finite-element data

arXiv:2607.13074v1 Announce Type: cross Abstract: This work studies the inverse problem of recovering the relative magnitudes of the tension, bending, and bearing loads acting on a crack from its stre

When T2I Synthetic Data Backfires: Amplified Privacy Risks in Real-Synthetic Mix Training

arXiv:2607.13541v1 Announce Type: cross Abstract: To overcome data scarcity and privacy constraints in data collection, it has become standard practice across academia and industry to augment real tra

With Argus Eyes: Assessing Retrieval Gaps via Uncertainty Scoring to Detect and Remedy Retrieval Blind Spots

arXiv:2602.09616v2 Announce Type: replace-cross Abstract: Reliable retrieval-augmented generation (RAG) systems depend fundamentally on the retriever's ability to find relevant information. We show th

A Behavioral State Vocabulary in Sony ERS-111 R-CODE

arXiv:2607.12115v1 Announce Type: new Abstract: This paper presents a corpus-level analysis of generated behavior diagrams derived from Sony's R-CODE sample distribution for the ERS-111 AIBO. Rather t

A Biomimetic Myoelectric Tentacle Prosthesis with Sensorless Object Detection and Vibrotactile Feedback

arXiv:2607.09807v2 Announce Type: replace Abstract: This paper presents the design and evaluation of a myoelectric tentacle-shaped prosthesis integrating electromyographic (EMG) control, sensorless ob

A hybrid analytical-PINN model for subsurface simulation of geothermal heat exchangers in heterogeneous underground

arXiv:2607.12271v1 Announce Type: new Abstract: In this paper, a parametric physics-informed neural network for solving the heterogeneous soil thermal problem with borehole heat exchangers (BHEs) as s

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs

arXiv:2602.19938v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) architectures are increasingly used to scale large language models efficiently, delivering strong accuracy under fi

A Shortcut to Statistically Steady-State Turbulence with Flow Matching

arXiv:2607.13022v1 Announce Type: cross Abstract: Many nonlinear physical systems exhibit an initial transient phase in which perturbations grow before nonlinear interactions lead to a statistically s

A Threshold Exceedance Framework for CBRN Uplift Evaluation in Frontier Language Models

arXiv:2607.12200v1 Announce Type: new Abstract: As frontier language models advance, policymakers and model developers need methods for assessing whether model access materially increases a non-expert

ABot-3DWorld 0: A Universal World Model to Explore Any 3D Space

arXiv:2607.11673v2 Announce Type: replace Abstract: We present ABot-3DWorld 0, a universal multimodal 3D world model that turns text, image, and video inputs into high-fidelity, explorable 3D worlds.

Accelerated Mixing Time of Randomized Hamiltonian Monte Carlo

arXiv:2607.12902v1 Announce Type: cross Abstract: We show the Randomized Hamiltonian Monte Carlo (RHMC) algorithm has accelerated mixing time guarantees for sampling from log-concave probability distr

Accelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques

arXiv:2607.12829v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a theoretical advantage in parallel generation over standard autoregressive models. However, parallel ge

ACID: Adaptive Caching for vIDeo generation

arXiv:2607.12358v1 Announce Type: new Abstract: Video diffusion models produce high-quality generations but remain slow at inference due to their sequential denoising procedure. Caching-based accelera

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter

arXiv:2607.10203v2 Announce Type: replace-cross Abstract: Adaptive-compute world models -- early-exit or mixture-of-depths predictors that spend variable depth per step -- assume depth buys better pre

Adversarial Attacks on Online Handwriting using Salience-based Temporal Editing

arXiv:2607.12500v1 Announce Type: cross Abstract: Deep learning models for online handwriting recognition have been shown effective and are increasingly deployed in practical applications. However, th

Affordance-Guided Diffusion Prior for 3D Hand Reconstruction

arXiv:2510.00506v2 Announce Type: replace Abstract: How can we reconstruct 3D hand poses when large portions of the hand are heavily occluded by itself or by objects? Humans often resolve such ambigui

An Omnilingual-ASR-Based Speech-LLM System for the 2nd MLC-SLM Challenge

arXiv:2607.12468v1 Announce Type: cross Abstract: We describe our submission to Task 1 of the 2nd MLCSLM Challenge: a cascaded diarization-then-recognition system that combines DiariZen-Large-s80 (Wav

Analysis of Mutual and Referential Human and Robot Gazes in a Collaborative Word Association Game

arXiv:2607.12181v1 Announce Type: new Abstract: Robot gaze is a major component of human-robot dialogue coordination. Most studies of gaze in human-robot dialogue focus on face-to-face social conversa

Analyzing Image Encoder Choices and Graph Homophily in GCN Frameworks for Breast Ultrasound Classification

arXiv:2607.12054v1 Announce Type: cross Abstract: Breast ultrasound is widely used for screening, yet automated analysis remains challenging due to speckle noise, acquisition variability, and weak sep

AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts

arXiv:2512.14461v2 Announce Type: replace Abstract: Sleep is essential for health, yet studying its dynamics requires manual sleep staging, a labor-intensive step in research and clinical care. Across

ARDepth: Auto-regressive Monocular Depth Estimation with Progressive Visual Conditioning

arXiv:2607.12433v1 Announce Type: cross Abstract: Diffusion models have recently become the dominant paradigm for monocular depth estimation (MDE). However, they implicitly assume that depth can be re

Audio-Native Speech Recognition with a Frozen Discrete-Diffusion Language Model

arXiv:2607.13013v1 Announce Type: new Abstract: Automatic speech recognition is dominated by autoregressive decoders that emit one token at a time. We ask whether a discrete diffusion language model c

AVQ-Attention: Adaptive Vector-Quantized Attention

arXiv:2607.12789v1 Announce Type: cross Abstract: The O(N^2) complexity of attention over N tokens remains a computational bottleneck in transformer models. Vector-Quantized (VQ) attention reduces thi

BAT-RM: A Boundary-Aware Transformer with Region-Aware Multi-Directional Mamba for Clinically Deployed Cervical Cancer Radiotherapy Auto-Contouring

arXiv:2607.11949v1 Announce Type: cross Abstract: We present a clinically deployed end-to-end auto-contouring system for cervical cancer radiotherapy planning, anchored by the Boundary-Aware Transform

BattVAE-GP: Generative Modeling of Long-Horizon Battery Degradation with Uncertainty Quantification

arXiv:2607.11943v1 Announce Type: cross Abstract: Long-horizon physics-based simulations of battery degradation provide mechanistic insight but remain computationally expensive, limiting their use for

Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Reddit

arXiv:2607.12383v1 Announce Type: new Abstract: Cancer-related discussions on social media provide an important space for information exchange and peer support, but also facilitate the spread of misin

researcharxiv-cs-cl

Beyond Logit Adjustment: A Residual Decomposition Framework for Long-Tailed Reranking

arXiv:2604.01506v2 Announce Type: replace Abstract: Long-tailed classification, where a small number of frequent classes dominate many rare ones, remains challenging because models systematically favo

Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model

arXiv:2409.10094v3 Announce Type: replace Abstract: Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e

Burst Spiking Neural Networks

arXiv:2607.11914v1 Announce Type: cross Abstract: A central goal of current Spiking Neural Network (SNN) research is to improve their accuracy toward becoming low-power alternatives to Artificial Neur

ChartGenEval: Corruption-Tested Multi-Dimensional Feedback for Rhythm-Game Chart Generation

arXiv:2607.12857v1 Announce Type: cross Abstract: A generated rhythm-game chart need not reproduce one official note sequence: many note choices can fit the same song and difficulty. Reference-note ag

CLaRa: Bridging Retrieval and Generation with Continuous Latent Reasoning

researchapple-ml-research

Retrieval-augmented generation (RAG) enhances large language models (LLMs) with external knowledge but still suffers from long contexts and disjoint retrieval–generation optimization. In this work, we

Cluster-Weighted EDMD

arXiv:2607.12243v1 Announce Type: new Abstract: Extended Dynamic Mode Decomposition (EDMD) approximates Koopman operators from data, but a single global operator is inefficient when different state-sp

Connected by Construction: Learning Tractable Near-Tour Marginals for Traveling Salesman Problems

arXiv:2607.12127v1 Announce Type: new Abstract: Learning-based methods for the traveling salesman problem (TSP) are often evaluated through the tours produced after decoding or search, but the learned

Constructed Reality, Contested Priors: Decoupling and the Architecture of Cognitive Relapse Under the Free Energy Principle

arXiv:2607.11958v1 Announce Type: new Abstract: Under the free energy principle, a predictive system does not observe reality directly; it maintains a generative model of the world and experiences tha

CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer

arXiv:2607.12750v1 Announce Type: new Abstract: Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer-related deaths globally, with approximately 1,9

Decentralized Gradient Descent: Bottleneck Regimes and Budget Complexity

arXiv:2607.12172v1 Announce Type: cross Abstract: Decentralized gradient descent (DGD) is widely used for solving distributed optimization problems over networks of agents. While its convergence prope

Deep Learning-based Surrogate Modelling of the LOD Method for Multiscale Problems

arXiv:2607.12570v1 Announce Type: cross Abstract: Multiscale problems are notoriously difficult to tackle using traditional numerical methods, as accurately resolving fine-scale features often require

Demonstration of the common dual-channel feature decoupling characteristic of front-door mediation causal inference methods in whole-slice image classification

arXiv:2607.12376v1 Announce Type: cross Abstract: Causal inference using front door intervention and multi-instance learning (MIL) has advanced the analysis of Whole Slide Images (WSI) in digital path

Diagrams-to-Dynamics (D2D): Exploring Causal Loop Diagram Leverage Points under Uncertainty

arXiv:2508.05659v4 Announce Type: replace Abstract: Background: Causal loop diagrams (CLDs) are widely used in health and environmental research to represent hypothesized causal structures underlying

Do We Really Need Transformers for Global Spatial Information Extraction in Traffic Forecasting?

arXiv:2607.12462v1 Announce Type: new Abstract: Existing traffic forecasting models commonly focus on extracting spatial dependencies, particularly global spatial information, which characterizes the

Do You Remember? Toward Memory-Centric Multimodal AI

arXiv:2607.11919v1 Announce Type: cross Abstract: Human memory is reconstructive, not a faithful recording. Current multimodal LLMs (MLLMs) lack this capability: they process images through a frozen v