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Understanding Role Switching in Human-AI Collaboration through Multimodal Behavioral Signals

arXiv:2509.20666v2 Announce Type: replace-cross Abstract: Human-AI collaboration often requires dividing complex tasks into complementary subtasks. As a task unfolds, users may want to shift which sub

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Uni-LaDiR: Latent Diffusion Unifies Multimodal Reasoning

DGX agent

arXiv:2609.19878v1 Announce Type: cross Abstract: Multimodal reasoning requires models to draw on information from multiple modalities throughout the reasoning process. Yet existing methods often conc

researcharxiv-cs-cl

18 Sept 2026

Walking on the Slope: Stable Bipedal Gaits with Genetic-Algorithm-Optimized Trajectories

arXiv:2609.20570v1 Announce Type: new Abstract: This paper presents the kinematic and dynamic modeling, trajectory generation, and stability analysis of an 8-degree-of-freedom (DOF) biped robot walkin

Watermarking Diffusion Language Models

arXiv:2509.24368v3 Announce Type: replace-cross Abstract: We introduce the first watermark tailored for diffusion language models (DLMs), an emergent LLM paradigm able to generate tokens in arbitrary

Well-posedness of neural turbulence closures and tangent dissipation

arXiv:2609.19647v1 Announce Type: cross Abstract: A neural turbulence closure defines a new boundary-value problem, R(U)=N(U)+F(U)=0, with a coupled Jacobian J(U)=N'(U)+F'(U), where N is the original

What Do Current Systematic Generalization Tasks Miss? A Reasoning-Centered Analysis

arXiv:2609.19212v1 Announce Type: new Abstract: Systematic generalization, the ability to solve novel problems by recombining known atomic elements, is central to human intelligence but difficult to s

When Data Imbalance Helps: Robust Generalization Through Shortcut Saturation

arXiv:2607.10116v2 Announce Type: replace-cross Abstract: We study robust generalization under spurious correlations: tasks where a shortcut feature is correlated with the true label in training but a

When Does Retrieval Help Time-Series Forecasting?

arXiv:2609.20193v1 Announce Type: new Abstract: Retrieval plug-ins supply a deep forecaster with information its lookback window cannot carry. Published evaluations report consistent gains, and each c

When2Think: Learning Difficulty-Aware Length Control for Efficient Hybrid Reasoning Models

arXiv:2609.19671v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex tasks but exhibit systematic inefficiency: they often overthink easy problems and un

WiC is Not WSD: A Study on LLMs and Lexical Ambiguity Resolution

arXiv:2609.20593v1 Announce Type: new Abstract: Word-in-Context (WiC) remains challenging for language models, despite recent progress on lexical-semantic tasks. We hypothesise that this difficulty ar

WiCleanData: Guaranteeing the Type Consistency of Wikidata by Taxonomy Refinement and Constraint Enforcement

arXiv:2609.20057v1 Announce Type: new Abstract: Because of its collaborative nature, Wikidata suffers from errors, in- consistencies, and excessive complexity, such as redundant classes, ambiguity bet

YNU-HPCC at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Using Multiple Prediction Headers

arXiv:2609.19238v1 Announce Type: cross Abstract: This paper describes the participation of the YNU-HPCC team in subtask A of task 11, Bridging the Gap in Text-Based Emotion at SemEval-2025. Our best-

Zarya: A Hybrid Autoregressive--Masked Diffusion Language Model with Flexible Training and Dual-Mode Inference

arXiv:2609.19868v1 Announce Type: cross Abstract: Autoregressive language models (ARMs) are constrained by sequential, left-to-right generation, while masked diffusion models (MDMs) enable parallel de

A Four-Stage Decomposition of Word-Problem Solving and Mechanistic Fragility in LLM Math Reasoning

arXiv:2609.17804v1 Announce Type: new Abstract: Large language models solve grade-school math word problems with high accuracy, yet a single irrelevant clause inserted into the problem can collapse it

A General Kernel Framework for Non-CND Distance Measures Using |D|-Dimensional Sparse Landmark Embeddings

arXiv:2609.19083v1 Announce Type: cross Abstract: Kernel methods, and Gaussian Processes (GPs) in particular, require a Hilbertian distance measure---one whose square is conditionally negative definit

A Gradient Flow Approach to Solving Inverse Problems with Latent Diffusion Models

arXiv:2509.19276v2 Announce Type: replace-cross Abstract: Solving ill-posed inverse problems requires powerful and flexible priors. We propose leveraging pretrained latent diffusion models for this ta

A Lightweight CNN Integrated Compact Convolutional Transformer for Multi-Scale Feature Learning and reducing computational complexity for breast cancer mammography image detection and classification

arXiv:2609.18212v1 Announce Type: cross Abstract: Over the years, Convolutional Neural Networks (CNNs) have demonstrated strong capability in cancer detection and classification using medical images.

A Non-Linear Neuron Based Detection of Isolated Pixels in Binary and Grayscale Images using Contrast Sensitive Receptive Fields

arXiv:2609.18399v1 Announce Type: cross Abstract: Identifying isolated points is important in image processing applications such as medical imaging, astronomy and quality control management. Other dom

A Scalable Framework for Automated NER Annotation Correction in Low-Resource Languages

arXiv:2609.18739v1 Announce Type: cross Abstract: Poor quality or noisy annotations in Named Entity Recognition (NER), as in any other NLP task, make it challenging to achieve state-of-the-art perform

A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyond

arXiv:2502.12048v4 Announce Type: replace Abstract: Decoding neural activity into human-interpretable representations is a key research direction in brain-computer interfaces (BCIs) and computational

A Systematic Evaluation of the COTQ Provincial Land Cover Product: Structural Consistency, Spectral Separability, and Relative Positioning Against ESA, ESRI, and Google Products

arXiv:2609.17731v1 Announce Type: new Abstract: High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management

A Taxonomy of Programming Languages for Code Generation

arXiv:2604.00239v3 Announce Type: replace Abstract: The world's 7,000+ languages vary widely in the availability of resources for NLP, motivating efforts to systematically categorize them by their deg

Accelerating Diffusion Sampling via Speculative Draft Trees

arXiv:2609.17691v1 Announce Type: cross Abstract: Speculative sampling accelerates diffusion model generation by drafting inexpensive candidate states and correcting them under a coupling that preserv

Accurate Trace Estimation with Fewer Random Bits via Recursive TensorSketch

arXiv:2609.18577v1 Announce Type: new Abstract: We consider the problem of estimating the trace of an implicit matrix mathbf{A} in R^{d^pimes d^p} that can only be accessed through matrix-vector produ

Active Learning Enables Generation of Molecules that Advance the Known Pareto Front

arXiv:2501.02059v2 Announce Type: replace Abstract: Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecu

Adaptive-MHE : A Sampling-Based Adaptive MPC for Legged Loco-Manipulation via Moving Horizon Estimation

arXiv:2609.17832v1 Announce Type: new Abstract: Legged robots have demonstrated a remarkable ability to traverse various terrains, yet generating effective loco-manipulation behaviors remains challeng

AfriSyCo: Measuring Assertive Framing, Verification, and Wording Sensitivity Around African-Language Content

arXiv:2609.17853v1 Announce Type: cross Abstract: AfriSyCo studies answer switching around African-language factual content with two complementary layers: native-language follow-ups and a controlled c

AI and Human Approaches to Mathematical Problem Solving

arXiv:2609.17779v1 Announce Type: cross Abstract: AI systems have begun to report solutions, disproofs, and substantive advances on long-standing mathematical problems, raising questions about whether

An operator splitting analysis of Wasserstein--Fisher--Rao gradient flows

arXiv:2511.18060v3 Announce Type: replace-cross Abstract: Wasserstein-Fisher-Rao (WFR) gradient flows have been recently proposed as a powerful sampling tool that combines the advantages of pure Wasse

Approximating High Dimensional Self-Motion Manifolds via Deep Generative Models

arXiv:2609.18169v1 Announce Type: new Abstract: Self-motion manifold (SMM) characterizes the geometric structure of the infinite inverse kinematic solutions set of a redundant manipulator at a fixed e

Approximation of the Basset force in the Maxey-Riley-Gatignol equations via universal differential equations

arXiv:2604.08194v2 Announce Type: replace Abstract: The Maxey-Riley-Gatignol equations (MaRGE) model the motion of spherical inertial particles in a fluid. They contain the Basset force, an integral t

ASPIRE: Asynchronous Batched Self-Speculative Decoding for Long-Context LLM Inference

arXiv:2609.17943v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by attention, whose repeated KV-cache reads make decoding memory-bound. Self-speculative decoding alleviate

Asymptotically Optimal Multi-Robot Task and Motion Planning

arXiv:2609.18813v1 Announce Type: new Abstract: Multi-robot task and motion planning (MR-TAMP) requires jointly reasoning about discrete task decisions and continuous collision-free motions of multipl

Bayesian Quadrature

arXiv:2602.16218v2 Announce Type: replace Abstract: Bayesian quadrature is a probabilistic, model-based approach to numerical integration, the estimation of intractable integrals, or expectations. Alt

Behavioral Fingerprinting and Navigation Prediction in Web Browsing

arXiv:2609.18273v1 Announce Type: new Abstract: Web browsing often appears ephemeral: users visit a few websites, complete a task, and move on. However, even short fragments of browsing activity can c

Benchmarking Tabular Foundation Models as Surrogates in Expensive Evolutionary Optimization

arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re

Beyond Accuracy: How Procedural Traces Shift the Decision Criterion of LLM Overseers

arXiv:2609.18204v1 Announce Type: cross Abstract: Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed st

Beyond frequency measures: Can contextual embeddings capture meaning change in scientific texts?

arXiv:2609.18804v1 Announce Type: new Abstract: Identifying technological trends is a core scientometric task, yet traditional frequency-based approaches struggle to capture substantial meaning shifts

Beyond Pixel Similarity: Task-Aware Evaluation of GAN-Based Synthetic Sonar Data for Robotic Perception

arXiv:2609.18100v1 Announce Type: cross Abstract: Synthetic data can reduce the cost of collecting and annotating training data for robotic perception, but generating sensor observations that preserve

Beyond Quadratic Loss: The Stability Phase Diagram of Adam

arXiv:2609.18314v1 Announce Type: new Abstract: Loss spikes are recurrent instabilities in neural-network training and can arise from multiple mechanisms. For Adam in particular, macroscopic loss spik

Beyond Truncation: Rethinking LLM Decoding as Ensemble Pruning

arXiv:2609.18723v1 Announce Type: new Abstract: We introduce Mahalanobis-Ensemble Decoding (ME-Decoding), a novel Large Language Model (LLM) decoding framework that frames candidate token selection as

Bracketing Uncertainty in Clustering Under the Manifold Hypothesis

arXiv:2609.17892v1 Announce Type: cross Abstract: The manifold hypothesis suggests a natural criterion for clustering: partition data according to the manifold component from which each point is drawn

Breaking the T^{2/3} Barrier for Sequential Calibration

arXiv:2406.13668v4 Announce Type: replace Abstract: A set of probabilistic forecasts is calibrated if each prediction of the forecaster closely approximates the empirical distribution of outcomes on t

Butterfly Effect and the Kinetic Energy Cascade in Probabilistic Machine Learning Weather Prediction Models

arXiv:2609.18489v1 Announce Type: cross Abstract: This study analyses kinetic energy (KE) spectra, difference kinetic energy (DKE) spectra, and signatures of KE transfer across spatial scales in four

CALIPER: Metric-Grounded Model-Free Recognition of Visually Similar Industrial Parts

arXiv:2609.17820v1 Announce Type: new Abstract: Fine-grained recognition of visually similar industrial parts is challenging when classes differ primarily in physical dimensions. Normalizing detected

researcharxiv-cs-cv

Can VLMs Reliably Assess Sidewalk Accessibility Attributes from Pedestrian-Level Imagery?

arXiv:2609.17882v1 Announce Type: cross Abstract: An important component of urban accessibility, particularly for wheelchair users and people with reduced mobility, is sidewalk compliance with measura

Capability Emergence Can Be Forecast: Per-Seed, In Advance, With Calibrated Intervals, Certified False Alarms, and a Blind Pre-Registered Gate

arXiv:2609.19000v1 Announce Type: new Abstract: Emergent capabilities are widely treated as unpredictable: loss improves smoothly while abilities appear abruptly. Prior work offers early-warning indic

CaSCo: Cascade-Aware Soft-Collision Motion Planning

arXiv:2609.18910v1 Announce Type: new Abstract: Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequence