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Three-Phase Scribble-Adaptive Curriculum Learning for autoPETV Grand Challenge

arXiv:2608.22096v1 Announce Type: new Abstract: This report describes Libo Zhang's algorithmic solution to autoPETV Grand Challenge on interactive lesion segmentation in whole-body PET/CT. Interaction

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To What Extent Does the Perceived Obesity Level of Humanoid Robots Affect People's Trust in Them?

DGX agent

arXiv:2411.06039v2 Announce Type: replace Abstract: Despite obesity being widely discussed in the social sciences, the effect of a robot's perceived obesity level on trust is not covered by the field

researcharxiv-cs-ro

25 Aug 2026

Token-Level Likelihood-Array Regression for Membership Inference and AI-Generated Text Detection

arXiv:2608.22179v1 Announce Type: cross Abstract: Membership inference asks whether a text was used to train a language model, whereas AI-generated text detection asks whether it was generated by a la

Tolerance-Dependent Inspection Disagreement Between a Fixed CMM and a Portable Articulated-Arm CMM

arXiv:2608.21404v1 Announce Type: new Abstract: Fixed coordinate measuring machines (CMMs) and portable articulated-arm CMMs are often assigned to the same inspection task, but their nominal accuracy

Tomatoes, Potatoes, and Onions: Questioning the Need for Faces in Face Presentation Attack Detection

arXiv:2608.21455v1 Announce Type: new Abstract: Face presentation attack detection (PAD) is traditionally formulated as a face-specific problem, although many of the visual artifacts introduced by pri

Topology of a Smile: Persistent Homology in Dental Imaging

arXiv:2608.21422v1 Announce Type: new Abstract: CBCT (Cone Beam Computed Tomography) scans provide detailed three-dimensional images, widely used in dentistry for diagnostic and treatment planning tas

ToSCA: Leveraging Hierarchical Reinforcement Learning on Temporal and Strategic Abstractions of Conversational Agents

arXiv:2608.21969v1 Announce Type: new Abstract: Humans have multiple levels of temporal abstractions on daily interaction and thinking, such as concept perception and strategic planning. Inspired by t

Toward a First-Principles Update Geometry for the Language-Model Head

arXiv:2608.22253v1 Announce Type: new Abstract: We study the language-model head and softmax as a single module, deriving an update geometry from their composition rather than from the weight matrix i

Toward a Foundation Plug-and-Play Prior for Computed Tomography Reconstruction via a Multimodal Diffusion Model

arXiv:2608.23190v1 Announce Type: new Abstract: Computed tomography (CT) throughput is limited by scan time, which grows with both the number of projections acquired and the detector integration time

Toward Effective and Reliable LLM Agents via Dynamic Ontology

arXiv:2608.22974v1 Announce Type: new Abstract: Large language model (LLM) agents rely heavily on knowledge encoded in model parameters or presented as unstructured context. In domain-specific tasks,

Towards a resource for multilingual lexicons: an MT assisted and human-in-the-loop multilingual parallel corpus with multi-word expression annotation

arXiv:2011.03783v3 Announce Type: replace-cross Abstract: In this work, we introduce the construction of a machine translation (MT) assisted and human-in-the-loop multilingual parallel corpus with ann

Towards insect-like distributed proprioception in actuators and appendages for flapping-wing insect-scale aerial robots

arXiv:2608.21699v1 Announce Type: new Abstract: Modern flapping-wing insect-scale air vehicles display agility similar to that of their insect counterparts; however, these impressive maneuvers are onl

Towards Safer Social Media Platforms: Scalable and Performant Few-Shot Harmful Content Moderation Using Large Language Models

arXiv:2501.13976v2 Announce Type: replace-cross Abstract: The prevalence of harmful content on social media platforms poses significant risks to users and society, necessitating more effective and sca

Traceable Spectral Inference via Influence Functions: Efficient Data Attribution and Error Proxies for the Ariel Mission

arXiv:2608.23458v1 Announce Type: new Abstract: Interpretability is critical for machine learning models deployed in scientific space missions such as ESA's Ariel, where ground truth is unavailable du

Training-Free Pseudo-Fusion for Composed Image Retrieval with Diffusion Models and Multimodal Large Language Models

arXiv:2608.23102v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) is an emerging paradigm in content-based image retrieval that enables users to formulate compositional queries by combini

Training-Free VLM Personalization via Calibrated Residual Decoding

arXiv:2608.22263v1 Announce Type: cross Abstract: Vision-language models can be personalized in a training-free manner by directly providing user profiles, preferences, or visual references at inferen

Training Large Language Models to Reason in a Continuous Latent Space

arXiv:2412.06769v4 Announce Type: replace Abstract: Large language models (LLMs) are typically constrained to reason in the language space, where they express the reasoning process through a chain-of-

Two-level domain-decomposition AdaGrad method for scalable training of graph neural networks

arXiv:2608.22575v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have emerged as a powerful framework for learning from graph-structured data. However, their efficient training remains c

Two Stage Wireless Federated LoRA Fine-Tuning with Sparsified Orthogonal Updates

arXiv:2505.00333v3 Announce Type: replace Abstract: Federated fine-tuning with low-rank adaptation (LoRA) communicates only two low-rank matrices instead of the full model, but existing methods typica

UNCLE-Grasp: A Task-Adapted Framework for Uncertainty-Aware Grasping of Leaf-Occluded Strawberries

arXiv:2601.14492v3 Announce Type: replace Abstract: Robotic strawberry harvesting remains challenging under partial occlusion, where leaves obscure fruit geometry and make grasp decisions based on a s

Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks

arXiv:2601.21242v2 Announce Type: replace-cross Abstract: Motivated by challenges in conditional generative modeling, where the target conditional density takes the form of a ratio f1 over f2, this pa

Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling

arXiv:2504.05216v4 Announce Type: replace-cross Abstract: Dense retrieval is a crucial task in Information Retrieval (IR), serving as the basis for downstream tasks such as re-ranking and augmenting g

UR^{2}-MLLM: Uncertainty-aware Revisit Reasoning in Multimodal Large Language Models for Radiology Report Generation

arXiv:2608.22217v1 Announce Type: new Abstract: Radiologists generate diagnostic reports through iterative and selective revisiting of suspicious regions to refine their interpretations. Recent multim

Variational Structure at the Edge of Stability

arXiv:2608.21660v1 Announce Type: new Abstract: When discrete-time optimizers operate at the edge of stability, they exhibit near-two-periodic behavior. These oscillatory dynamics are reminiscent of c

Vehicle speed dataset for the major European road network derived from Sentinel-2 imagery, 2022-2026

arXiv:2608.22116v1 Announce Type: new Abstract: The dataset provides individual vehicle speed observations on European E-roads: motorways, trunk roads, primary and secondary roads, as tagged in OpenSt

VersaDB: A High-Performance AI Storage Database for Unifying Mutimodal Datasets

arXiv:2608.22795v1 Announce Type: new Abstract: The AI field has been rapidly developing, leading to the emergence of a large number of AI training datasets of various types. These datasets contain di

VibrantLeaves: A principled parametric image generator for training deep restoration models

arXiv:2504.10201v3 Announce Type: replace Abstract: In this paper, we introduce a synthetic image generator relying on a few simple principles, specifically focusing on geometric modeling, textures, a

VisAdj: Learning Adjacency Matrices from Node-Link Images

arXiv:2608.21825v1 Announce Type: new Abstract: Learning adjacency matrices from node-link images is a fundamental problem for recovering structured graph information from visual observations. Existin

Vision-Guided Morphing Quadcopter for Multi-Geometry Payload Transport through Narrow Passages

arXiv:2608.21879v1 Announce Type: new Abstract: Aerial payload transport using multirotor unmanned aerial vehicles is challenging because payload geometry, contact interaction, grasp stability, flight

VisionCoach: Reinforcing Grounded Video Reasoning via Visual-Perception Prompting

arXiv:2603.14659v2 Announce Type: replace-cross Abstract: Video reasoning requires models to locate and track question-relevant evidence across frames. While reinforcement learning (RL) with verifiabl

VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection

arXiv:2602.13880v2 Announce Type: replace Abstract: Graph property detection aims to determine whether a graph exhibits certain structural properties, such as being Hamiltonian. Recently, learning-bas

WARP: Wasserstein-Aligned RAG for Population Opinions

arXiv:2608.22859v1 Announce Type: cross Abstract: RAG systems are increasingly used to summarize what large collections of documents say. A user asks 'What do people think about X?' and receives an an

What AstroPT knows about galaxies, and what that can teach us about LLMs

arXiv:2608.22614v1 Announce Type: new Abstract: Interpretability research increasingly asks when concepts emerge during training and whether linear probes recover real structure, but in language model

What Does Activation Steering Control? Attribution Across Answer Encodings and Output-Sensitive Subspaces

arXiv:2608.22985v1 Announce Type: new Abstract: Activation steering is often evaluated under the answer encoding used to construct the direction. A reported gain may reflect the intended judgment or c

What is an intelligent system?

arXiv:2009.09083v4 Announce Type: replace-cross Abstract: The term intelligent system has emerged in the field of information technology as a category of computer systems derived from successful appli

What is mathematics now, and what should it be?

arXiv:2608.23218v1 Announce Type: new Abstract: Advances in neural theorem provers have been impressive, but the successes obscure a broader vision of what AI can do for mathematics and how mathematic

What is the effect of running-specific prostheses on long jumps? Optimization-based prediction and analysis using biomechanical models

arXiv:2608.22507v1 Announce Type: new Abstract: Long jumpers with below the knee amputation (BKA) that take off from their running-specific prosthesis (RSP) improved performances significantly over th

What Models Know, How Well They Know It: Knowledge-Weighted Fine-Tuning for Learning When to Say 'I Don't Know'

arXiv:2604.05779v2 Announce Type: replace-cross Abstract: While large language models (LLMs) demonstrate strong capabilities across diverse user queries, they still suffer from hallucinations, often a

What Neural Network Field Theory Can and Cannot Realise on a Computer

arXiv:2608.21523v1 Announce Type: cross Abstract: One aim of neural network field theory is to put a quantum or effective field theory on a computer, with the network ensemble itself as the theory. We

When Do VLMs Help Arabic Manuscript OCR? A Cross-Dataset Study

arXiv:2608.22366v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being used for document understanding, yet their role in Arabic and Islamic manuscript recognition remain

When More Modalities Hurt: Modality Dropout for Heavy-Duty Vehicle Engine Diagnostics

arXiv:2608.23161v1 Announce Type: new Abstract: Heavy-duty vehicle diagnostics generate three disconnected data modalities: unstructured multi- lingual service complaints, high-dimensional sensor tele

When More References Hurt: Contamination-Aware DINOv2 Memory Banks for Few-Shot Steel Defect Detection

arXiv:2608.22082v1 Announce Type: new Abstract: Patch-memory anomaly detectors assume that their reference bank is normal, an assumption that is difficult to guarantee when additional industrial image

When Persona Simulations Are Informative: Graph-Structured Signals for Pluralistic Opinion Sensing

arXiv:2608.22438v1 Announce Type: new Abstract: Persona-conditioned large language models (LLMs) are increasingly used to simulate survey responses across diverse domains. However, apparent response v

Where Cognition Lives: Dissecting Emergent from Computed Function in a Minimal Complete Cognitive Architecture

arXiv:2608.22347v1 Announce Type: new Abstract: A cognitive architecture is more than the module that reasons: it must also decide how long to think and what deserves the effort. We built a minimal bu

Which Histories Matter for Time Series Forecasting? Learning Predictive Relevance with Future Supervision

arXiv:2608.23221v1 Announce Type: cross Abstract: Historical retrieval for time-series prediction commonly treats past similarity as a proxy for usefulness. We ask a different question: which historic

Whitewashing Hate, Smearing Harmless Content: Annotator-Style Rebuttal Attacks on LLM-Based Moderation

arXiv:2608.22230v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for hate speech moderation, often within human--AI workflows in which reviewers provide feedback befo

Who Should Teach? Confidence-Aware Dual-Teacher Learning for Few-Shot Node Classification on Text-Attributed Graphs

arXiv:2608.22127v1 Announce Type: new Abstract: Text-Attributed Graphs (TAGs) integrate graph structures and node-associated textual attributes, and recent studies have increasingly leveraged Large La

Why Does Robustness Reduce Superposition?

arXiv:2608.22155v1 Announce Type: cross Abstract: The study of adversarial examples and their origins remains an open area of research. Mechanistic interpretability, and superposition in particular, o