Search: “research”

APTER: Adaptive Post-Training with Expert-Grounded Rubrics

arXiv:2608.14212v1 Announce Type: new Abstract: As large language models enter professional domains, they must satisfy domain constraints, include critical evidence, and provide complete reasoning rat

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Architecture and Affordances of PLAUD: Performative Latents and Unsupervised DDSP

DGX agent

arXiv:2608.13724v1 Announce Type: cross Abstract: PLAUD (Performative Latents and Unsupervised DDSP) is a neural synthesizer and Max for Live instrument for live electronic music, built on NoiseBandNe

researcharxiv-cs-lg

17 Aug 2026

Asymmetric Discourse Homogenization and Shared Language Technology: Evidence from Reddit

arXiv:2608.13674v1 Announce Type: cross Abstract: I document an ideologically asymmetric break in the pre-existing diversification trend of political discourse, emerging around late 2022, using 6 mill

researcharxiv-cs-cl

Automated Inference of Graph Transformation Rules

arXiv:2404.02692v3 Announce Type: replace-cross Abstract: The explosion of data available in life sciences is fueling an increasing demand for expressive models and computational methods. Graph transf

BCMT: Blockwise Causal Memory Transformer

arXiv:2608.13578v1 Announce Type: cross Abstract: Transformer architectures rely on dense self-attention to model long-range dependencies, but this mechanism exhibits quadratic complexity with respect

BGA: A noise-immune neural distillation framework for malicious signature extraction in high-entropy encrypted flows

arXiv:2608.14126v1 Announce Type: cross Abstract: To mitigate attention dilution in high-entropy TLS 1.3 flows, we propose BGA, a noise-immune neural distillation framework for encrypted threat intell

BICPO-VLA: Behavior-Identified Continuation Preference Optimization for Smooth Asynchronous Vision-Language-Action Control

arXiv:2608.13924v1 Announce Type: new Abstract: The request-to-handoff gap has three coupled sources: ambiguity about the behavior intended at request time, physical-state drift accumulated during act

researcharxiv-cs-ro

Body size predicts how long ant workers live - but not how they age or how they die from heat

arXiv:2608.14245v1 Announce Type: cross Abstract: In social insects, mortality risk comprises distinct components that may not share the same predictors: lifespan duration, senescence trajectory, and

Boosting Data Augmentation with Stochastic Weight Averaging

arXiv:2608.14373v1 Announce Type: new Abstract: The symmetries of a learning task have become an important factor in designing modern deep learning solutions. Data augmentation is a straightforward an

Capacity-Dependent Effects of Data Selection for Reasoning

arXiv:2608.13721v1 Announce Type: cross Abstract: In reasoning supervised fine-tuning, candidate responses for the same instruction can differ substantially in how well they match the student's curren

Catching the Imposter: Self-Supervised Learning of Physical Coherence with Cross-Entity Feature Permutations

arXiv:2608.14372v1 Announce Type: new Abstract: Scientific data often describe entities whose features are jointly governed by the laws of physics, yet existing self-supervised learning (SSL) objectiv

Classical Limits of Spectral Filtering in Quantum Generative Models

arXiv:2608.14169v1 Announce Type: cross Abstract: Spectral filtering has been proposed as a route to regularization in quantum generative models: the quantum Fourier transform exposes the amplitude sp

CoANeRV: Coordinate-Aware Token-Space Neural Video Representation

arXiv:2608.13938v1 Announce Type: new Abstract: Neural representations for videos (NeRV) have shown strong reconstruction fidelity by storing video-specific information in network weights. However, ex

Communication in modular robotic motor control: Bilateral controllers under realistic constraints

arXiv:2608.13904v1 Announce Type: new Abstract: Robotic motor control in musculoskeletal systems requires fast, accurate movement and robust postural stabilization under signal-dependent noise (where

researcharxiv-cs-ro

Concept Guidance: Precise, Training-Free Latent Control for Text-to-Image Generation

arXiv:2608.14172v1 Announce Type: cross Abstract: Text-to-image diffusion models have two major drawbacks that severely limit their practical utility: (1) standard models lack an intrinsic mechanism f

Concept Unlearning by Modeling Key Steps of Diffusion Process

arXiv:2507.06526v4 Announce Type: replace Abstract: Text-to-image diffusion models remain susceptible to generating undesirable or harmful content. Although concept unlearning mitigates this risk, exi

Conditional Neural Optimal Transport for Predicting Cellular Phenotypes from Molecular Structure

arXiv:2608.14293v1 Announce Type: new Abstract: High-content microscopy enables systematic profiling of cellular responses to chemical perturbations, but the scale of the chemical space makes exhausti

Connected Subspace Clustering: Hardness, a Scalable Heuristic, and an Application to Sea Level Geodesy

arXiv:2608.14215v1 Announce Type: new Abstract: Constrained optimization extends classical optimization by integrating side information, making it widely applicable across scientific and engineering d

Context Aware AI Assistant and AR Interface for Lunar Extravehicular Activity (EVA) Procedural Guidance

arXiv:2608.13589v1 Announce Type: cross Abstract: As human space exploration returns to the Moon, astronauts need rapid access to procedural information during extravehicular activities (EVAs), where

Continual Evolution Strategies in Control Tasks

arXiv:2608.13600v1 Announce Type: cross Abstract: We study Evolution Strategies (ES) for continual control, where agents must adapt to changing tasks without forgetting previous ones. On sequential Mu

Contrastive Learning for Interpretable Anomaly Detection at Collider Experiments

arXiv:2608.13652v1 Announce Type: new Abstract: Generic event-level anomaly detection for collider physics has two recurring problems: anomaly scores are hard to interpret, and they correlate strongly

CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets

arXiv:2608.14403v1 Announce Type: new Abstract: Subject-driven image personalization---generating new images that preserve the identity of one or several reference subjects in novel scenes---is a foun

CSG-Mamba: A Convolutional Scoring Gating Vision State Space Network for Endoscopic Polyp Segmentation

arXiv:2608.14146v1 Announce Type: new Abstract: Accurate polyp segmentation is critical for computer-aided colonoscopy, yet endoscopic images often contain low-contrast boundaries, mucosal texture int

Data-driven techniques for translational neuroscience and personalized neuro-health

arXiv:2608.13749v1 Announce Type: cross Abstract: Neurodegenexrative diseases such as Alzheimer's disease and Parkinson's disease are diagnosed most reliably only after substantial, often irreversible

Decoding the Past: An Uncertainty-Aware Deep Learning Framework for Sex Attribution in Prehistoric Hand Stencils

arXiv:2608.14539v1 Announce Type: cross Abstract: Determining the biological sex of the individuals who created Upper Paleolithic hand stencils remains a challenging problem due to the absence of grou

Demonstration of Space Robot Teleoperation over a Lossy and Delayed Network using ATMOS

arXiv:2608.14031v1 Announce Type: new Abstract: We present a demonstration showcasing the Autonomy Testbed for Multi-purpose Orbiting Systems (ATMOS), a planar spacecraft-analog robot designed for har

researcharxiv-cs-ro

Designing Compact Neural Architectures via Neuron Gating and Mixed Activation

arXiv:2608.14443v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) is naturally formulated as a bilevel optimization problem, where the upper-level optimizes the architecture using val

Does ISO-Grounded NFR Specification Improve LLM Code Generation? A Comparison of Rich and Structured Interventions against a Natural-Language Baseline

arXiv:2608.13742v1 Announce Type: cross Abstract: In LLM-based code generation, Non-Functional Requirements (NFRs) are often specified as terse one-line phrases. We ask whether grounding those specifi

Model Releases

Don't Claim Benchmark-Oriented Optimization Improves General Coding Capability -- Diverse Evaluation Is Required

model-releasesarxiv-cs-ai

arXiv:2608.13566v1 Announce Type: cross Abstract: Post-training papers, model cards, and blog posts often treat scores on a small set of coding benchmarks (e.g., SWE-bench and LiveCodeBench) as eviden

Early Stopping for Large Reasoning Models via Confidence Dynamics

arXiv:2604.04930v2 Announce Type: replace-cross Abstract: Large reasoning models rely on long chain-of-thought generation to solve complex problems, but extended reasoning often incurs substantial com

EEG-PRISM: Physiologically-Grounded Interpretability of Predictions by EEG Foundation Models

arXiv:2608.13676v1 Announce Type: new Abstract: Objective: Foundation models represent the next advancement in AI for EEG analysis; however current explainable AI techniques provide attribution scores

Emergent Models: Intelligence from Tiny Substrates

arXiv:2608.14019v1 Announce Type: cross Abstract: Emergent Models (EMs) are a machine learning paradigm based on simple yet open-ended substrates, such as cellular automata, in which modeling is treat

Face Re-morphing: Differential Morphing Attack Detection via Feature-Space Similarity Changes

arXiv:2608.13858v1 Announce Type: new Abstract: Face morphing attacks pose a serious threat to face recognition systems because a single morphed document image can be matched to multiple contributors.

Fashion Outfit Generation via Unified Sequential Composition Models

arXiv:2608.13888v1 Announce Type: new Abstract: The task of synthesizing stylistically coherent fashion outfits from massive item libraries, known as fashion outfit generation, remains a non-trivial c

Fast Implicit Neural Light Field Representation via Geometric Decomposition and Multi-Resolution Low-Rank Features

arXiv:2608.13949v1 Announce Type: new Abstract: Implicit neural representations provide a compact and continuous way to reconstruct dense light fields from sampled ray coordinates. However, fast light

FIRM: Fine-Grained Intra-Token Representation of Masks for Remote Sensing Reasoning Segmentation

arXiv:2608.13980v1 Announce Type: new Abstract: Reasoning segmentation requires multimodal large language models (MLLMs) to translate implicit instructions into precise pixel-level masks. MLLMs encode

FLARE MCMC: Fidelity-based Layer-Adaptive REcursive proposals for MCMC

arXiv:2608.13774v1 Announce Type: new Abstract: Markov chain Monte Carlo (MCMC) requires only the ability to evaluate the likelihood, making it a common technique for inference in complex models. Howe

FreeBalance: Pre-Routing Online Moe Load Balancing via Residual Workload Prediction

arXiv:2608.14205v1 Announce Type: new Abstract: Load imbalance poses a major bottleneck to the efficiency of expert parallelism in distributed inference of Mixture-of-Experts (MoE) models. The most he

From crown candidates to neighborhood screening: integrating optical GeoAI and spatial modeling for urban-canopy assessment in Davis, California

arXiv:2608.13856v1 Announce Type: cross Abstract: Timely urban-canopy information is essential for linking remote sensing with heat, mobility, and neighborhood planning. We developed an optical GeoAI

From Fixed Grids to Moving Particles:A Transferable Latent Operator for Fluid Dynamics

arXiv:2608.14120v1 Announce Type: cross Abstract: Lagrangian modeling is vital to fluid dynamics, as it characterizes particle transport and complements the Eulerian description.However, Lagrangian tr

From Style Replication to Style Exploration: Enabling Art Style Exploration with Analyze-Experiment-Resituate Framework

arXiv:2608.14405v1 Announce Type: cross Abstract: Art style is a signature of professional digital artists that develops through repeated experimentation, reflection, and adaptation. While generative

Generative Modeling with Bayesian Sample Inference

arXiv:2502.07580v4 Announce Type: replace Abstract: We present a novel view of diffusion-like generative modeling from the perspective of iterative Gaussian posterior inference. By treating the genera

Geometric Filtering of LLM-Generated Samples for Few-Shot Text Classification

arXiv:2608.13866v1 Announce Type: cross Abstract: Large language models (LLMs) can generate synthetic training data for text classification, but the quality of generated samples is heterogeneous: some

researcharxiv-cs-cl

Grounding Without Corrective Control: Truth-Tracking Profiles for Large Language Models

arXiv:2608.14252v1 Announce Type: new Abstract: Recent work suggests that some large language model representations have content or reference. Grounding can secure either without supplying live routes

Hard Cases, Bad Labels: Testing Error Exposure and Error Location in Uncertainty Sampling Under Bounded Label Noise

arXiv:2608.13601v1 Announce Type: new Abstract: Active learning can reduce labeling cost by selecting informative examples, but the most uncertain examples may also be the hardest to label correctly.

HI-MeshGraphNets: Efficient and Accurate Mesh-based Physics Learning with Hierarchical Multi-scale Graph Neural Networks

arXiv:2608.13827v1 Announce Type: new Abstract: Machine-learned physical surrogate models have become promising alternatives to mesh-based numerical solvers. Among them, graph neural networks (GNNs) a

Hybrid Quantum-inspired Kolmogorov-Arnold Networks for Privacy-Aware Federated Biosignal Learning

arXiv:2608.13914v1 Announce Type: cross Abstract: Electrocardiogram (ECG) recordings are sensitive biomedical data, limiting the ability of hospitals and wearable devices to share raw signals for cent

Identifiability and Order-Dimension Limits of In-Context Learning on Partial Orders

arXiv:2608.14004v1 Announce Type: new Abstract: In-context learning is commonly formalized as inference from examples of a function. Partial orders instead combine transitivity, antisymmetry, and inco