Search: “research”

MolGVR: A Chemistry-Grounded Framework for Text-to-Molecule Generation

arXiv:2607.29479v1 Announce Type: new Abstract: Text-to-molecule generation is typically formulated as a one-shot sequence generation problem, where a model directly maps target descriptions to molecu

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Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks

DGX agent

arXiv:2505.21736v2 Announce Type: replace Abstract: Translation equivariance is a central reason convolutional neural networks have been successful in computer vision. Other symmetries, such as rotati

researcharxiv-cs-cv

3 Aug 2026

Multi-Granularity Position Embedding of Graphs via Granular-Ball for Link Prediction

arXiv:2607.29115v1 Announce Type: cross Abstract: Link prediction aims to identify potential or future connections within a given graph structure. Position information is essential for link prediction

Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies

arXiv:2401.04890v2 Announce Type: replace-cross Abstract: This work introduces a novel principle for disentanglement we call mechanism sparsity regularization, which applies when the latent factors of

OASIS: Occlusion-aware Single-image Hand Avatar Reconstruction via 3D Gaussian Splatting

arXiv:2607.29633v1 Announce Type: new Abstract: Single-image 3D hand avatar reconstruction is fundamentally ill-posed and particularly challenging due to limited visual evidence under severe self-occl

On the Expressive Power of Sparse Geometric MPNNs

arXiv:2407.02025v5 Announce Type: replace-cross Abstract: Motivated by applications in chemistry and other sciences, we study the expressive power of message-passing neural networks for geometric grap

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation

arXiv:2603.17205v3 Announce Type: replace-cross Abstract: Domain-specific finetuning is essential for dense retrievers, yet not all data pairs contribute equally to the learning process. We introduce

Optical Flow Sensor: A Direction-Selective Bionic Retina Design

arXiv:2607.28686v1 Announce Type: cross Abstract: Optical flow characterizes motion in the visual field and is fundamental to motion perception and tracking in biological and artificial vision systems

Ordered-to-disordered transfer learning with graph neural networks for formation-energy and HOMO-LUMO gap prediction in high-entropy perovskite oxides

arXiv:2607.29510v1 Announce Type: cross Abstract: High-entropy perovskite oxides (HEPOs) represent a chemically complex class of materials with promising functional properties, yet their vast composit

Physics-Embedded Neural ODEs for Learning Antagonistic Pneumatic Artificial Muscle Dynamics

arXiv:2602.23670v2 Announce Type: replace Abstract: Pneumatic artificial muscles (PAMs) enable compliant actuation for soft wearable, assistive, and interactive robots. When arranged antagonistically,

researcharxiv-cs-ro

PhyUnfold-Net: Advancing Remote Sensing Change Detection with Physics-Guided Deep Unfolding

arXiv:2603.19566v3 Announce Type: replace Abstract: Bi-temporal change detection is highly sensitive to acquisition discrepancies, including illumination, season, and atmosphere, which often cause fal

PiDDM: Physics-Informed Differentiable Degradation Modeling for Lithium-Ion Battery State-of-Health Prediction

arXiv:2607.29095v1 Announce Type: new Abstract: Accurate prediction of lithium-ion battery state of health (SOH) is essential for reliable energy storage operation. However, purely data-driven models

Progressive Checkerboards for Autoregressive Multiscale Image Generation

arXiv:2602.03811v3 Announce Type: replace Abstract: A key challenge in autoregressive image generation is to efficiently sample independent locations in parallel, while still modeling mutual dependenc

Provable Diffusion Posterior Sampling for Bayesian Inversion

arXiv:2512.08022v2 Announce Type: replace-cross Abstract: We propose a novel diffusion-based posterior sampling method within a plug-and-play framework. Our approach constructs a probability transport

PTP: Previous-Token Prediction based LLM Inversion for Near-Exact Prompt Reconstruction

arXiv:2607.29378v1 Announce Type: new Abstract: Large language models (LLMs) generate text by auto-regressively sampling the next token. This inherently leads to a many-to-many mapping between prompts

Pyramidal Width Can Increase Under Vertex Insertion

arXiv:2607.29555v1 Announce Type: new Abstract: Lacoste-Julien and Jaggi conjectured in 2015 that the pyramidal width of a polytope cannot increase when a vertex is added, provided that every old poin

RAID: Towards Robust AI-Generated Image Detection with Bit-Reversed Images

arXiv:2607.28974v1 Announce Type: cross Abstract: The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To p

ReMoE: Report-Guided Mixture-of-Experts for Multimodal OCT/OCTA Anomaly Detection

arXiv:2607.29039v1 Announce Type: new Abstract: Multimodal medical anomaly detection identifies samples deviating from normal patterns, where scarce abnormal cases make normality modeling from normal

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation

arXiv:2607.28776v1 Announce Type: new Abstract: Generative machine learning is increasingly used for inorganic crystal structure generation. Most models and the corresponding evaluation approaches rel

ResKV: Reconstructing Omitted Attention Contributions for Fixed-Budget KV Cache Compression

arXiv:2607.29591v1 Announce Type: new Abstract: KV cache compression is essential for efficient long-context inference. Existing eviction methods permanently discard unselected tokens and consequently

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning

arXiv:2606.13316v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a central technique for improving long-horizon reasoning in Large Language Models (LLMs). H

Role-Break in Attention Heads: Understanding and Detecting Hallucinations in VLMs

arXiv:2607.29412v1 Announce Type: new Abstract: Despite remarkable progress in vision-language generation, Vision-Language Models (VLMs) remain prone to hallucinations, producing content that is incon

SATViz: Real-Time Visualization of Clausal Proofs

arXiv:2209.05838v2 Announce Type: replace Abstract: Visual layouts of graphs representing SAT instances can highlight the community structure of SAT instances. The community structure of SAT instances

SCMA: Structure-Conditioned and Metal-Aware Flow Matching for CT Metal Artifact Reduction

arXiv:2607.28759v1 Announce Type: cross Abstract: In X-ray CT, metallic objects cause beam hardening, photon starvation, and scattering, leading to projection inconsistency, streaks, dark bands, and s

Seeing Differently: Modeling Interpretive Perspectives in Computational Creativity using a Four-World Framework

arXiv:2607.28644v1 Announce Type: cross Abstract: Creativity in computational systems is often evaluated as an objective property of artifacts, with existing Computational Creativity (CC) frameworks a

Shapley-Value-Based Feature Attribution for Data Masking

arXiv:2607.28946v1 Announce Type: new Abstract: Despite its many benefits, widespread access to individuals' personal data also causes severe privacy concerns for consumers, companies, and policymaker

Side-Channel Attacks Survive Noise Cancellation in 3D Printers

arXiv:2606.13952v2 Announce Type: replace-cross Abstract: Active Motor Noise Cancellation (AMNC) is a noise-reduction feature shipped in commercial fused deposition modeling (FDM) 3D printers. Because

Simulative Anomaly Detection using 2D Tomography

arXiv:2607.28701v1 Announce Type: cross Abstract: We present a novel technique for predicting the imaging quality of anomalies such as cancer cells located inside organic tissues. This technique is us

SPICE: Synergy and Partial Information Based Curriculum Evolution

arXiv:2606.16639v2 Announce Type: replace Abstract: Multimodal learning exploits complementary information across heterogeneous modalities. The informativeness of each modality can vary widely across

Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens

arXiv:2607.29363v1 Announce Type: cross Abstract: Balancing sequence length, representational capacity, and long-horizon stability is a central problem in autoregressive (AR) speech and audio generati

Stem: Rethinking Causal Information Flow in Sparse Attention

arXiv:2603.06274v2 Announce Type: replace-cross Abstract: The quadratic computational complexity of self-attention remains a fundamental bottleneck for scaling Large Language Models (LLMs) to long con

Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis

arXiv:2607.28903v1 Announce Type: cross Abstract: Variance-based global sensitivity analysis (GSA) plays a key role in uncertainty quantification by identifying the contributions of uncertain inputs t

Sycophancy Undermines Epistemic Vigilance in Cooperative Vision-Language Tasks

arXiv:2607.29585v1 Announce Type: new Abstract: To maintain common ground in cooperative conversation, humans iteratively update their beliefs as conversation participants share new information; parti

Symplectic Representation of Legendre Dynamics

arXiv:2512.19409v2 Announce Type: replace Abstract: Modern learning systems act on internal representations of data, yet how these representations encode underlying physical or statistical structure i

TAVI-TEC: An AI-Based Tool for Procedural Planning of Transcatheter Aortic Valve Implantation

arXiv:2607.29243v1 Announce Type: cross Abstract: Computed tomography angiography (CTA) is crucial for preprocedural TAVI planning, providing the anatomical information required for prosthesis sizing

Technological Advances in Detecting and Managing Cognitive Impairment in Older Adults: Trends, Challenges, and Future Directions

arXiv:2607.28687v1 Announce Type: cross Abstract: As populations age, cognitive decline from mild cognitive impairment (MCI) to dementia is a defining health challenge of the coming decades, yet routi

Tensor Data Scattering and the Impossibility of Slicing Theorem

arXiv:2012.01982v3 Announce Type: replace Abstract: This paper proposes a standard way to represent sparse tensors. A broad theoretical framework for tensor data scattering methods used in various dee

TFGformer: Multivariate Time Series Forecasting via Time-Frequency Graph Learning and Covariate Fusion

arXiv:2607.29459v1 Announce Type: cross Abstract: Large-scale multivariate time series from heterogeneous IoT sensors demand accurate long-term forecasting for resource scheduling and predictive maint

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale

arXiv:2607.14144v2 Announce Type: replace Abstract: The Platonic Representation Hypothesis (PRH) holds that as models scale, representations of heterogeneous networks converge toward a shared model of

The persuasive power of large language models does not depend on their perceived national origin

arXiv:2607.29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as fo

ThinkReset: Learnable Intermediate Interface Construction for Bounded-Context Long-Horizon Reasoning

arXiv:2607.28642v1 Announce Type: new Abstract: Long chain-of-thought reasoning improves performance on complex problems, but it also introduces redundancy accumulation, context overflow, and error an

Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering

arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r

TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs

arXiv:2607.28640v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) should generate consistent responses given semantically equivalent inputs across modalities. However, we observ

TORUS: A Test of Rendering-Understanding Self-Coherence for Unified Audio Models

arXiv:2607.28896v1 Announce Type: cross Abstract: Unified audio models capable of audio understanding, audio generation and, increasingly, audio editing are proliferating rapidly. Yet a basic question

Toward Robust and 3D-Aware RGB-NIR Imaging in the Dark

arXiv:2607.29684v1 Announce Type: new Abstract: Robust low-light imaging remains challenging for the community. Recent studies have explored fusing Near-Infrared (NIR) with noisy RGB to achieve improv

Towards the Holographic Characteristic of LLMs for Efficient Short-text Generation

arXiv:2601.22546v2 Announce Type: replace-cross Abstract: The recent advancements in Large Language Models (LLMs) have attracted interest in exploring their in-context learning abilities and chain-of-

Training-Free Entity-Level Few-Shot Segmentation of Remote Sensing Images with Advection Refinement

arXiv:2607.29278v1 Announce Type: new Abstract: Existing cross-domain few-shot segmentation approaches suffer from high training costs due to source-domain episodic training and pixel-wise dense predi

Uncertainty-Aware Deepfake Detection via Multi-View Structural Learning

arXiv:2607.28769v1 Announce Type: new Abstract: Security-critical biometric and forensic applications require accurate predictions and reliable confidence estimates, particularly under distribution sh