Search: “research”

Pair-Level Essay-Scale Republication and Reuse from Fragmented Historical Text Reuse: A Workflow Study on Eighteenth-Century Books and Newspapers

arXiv:2608.27343v1 Announce Type: new Abstract: This paper addresses the recovery of essay-scale republication and reuse from fragmented text-reuse evidence, a setting whose central challenge is pair-

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Research

Per-View Gaussian Predictions Enable Training-Free Distractor Filtering in Feed-Forward 3DGS

DGX agent

arXiv:2608.26951v1 Announce Type: cross Abstract: Feed-forward 3D Gaussian Splatting reconstructs an explicit Gaussian representation from multiple input images in one network execution, making 3D rec

researcharxiv-cs-ai

28 Aug 2026

Persona-Execution Separation: An Architecture Pattern for Evolving LLM Agents under Execution Audit

arXiv:2608.27427v1 Announce Type: cross Abstract: Large language model (LLM) agents in governed organizations must let the persona (instructions, tone, self-presentation) evolve freely, while keeping

Planning a Shared Modular Fixture Layout Across Robotic Disassembly Stages

arXiv:2608.27151v1 Announce Type: new Abstract: Stable support remains challenging in robotic disassembly of irregularly shaped products. As components are progressively removed, the available support

Planting a Latent Variable in Natural-Looking Text: a More Realistic Test of Belief States in LLMs and Their Link to Concept Geometry

arXiv:2608.26887v1 Announce Type: new Abstract: LLMs are thought to track 'belief states,' i.e., running probability distributions over the latent variables that govern language (Shai et al., 2024; Sa

Pneumatic-Tomographic Tactile Skin for Multicontact Localization and Force Estimation

arXiv:2503.13036v3 Announce Type: replace Abstract: Tactile skins based on electrical impedance tomography (EIT) enable large-area contact localization with few electrodes, but suffer from nonuniform

PragAlign: Evidence-Sensitive Reply Assistance Across Chinese and Japanese Appropriateness Judgments

arXiv:2608.26700v1 Announce Type: new Abstract: Reply assistance in multilingual settings requires linguistic competence and culturally situated judgments of appropriateness. We present PragAlign, whi

Predicting Quantifiability from Primary Screens to Prioritize Dose-Response Profiling

arXiv:2608.26538v1 Announce Type: new Abstract: High-throughput drug screening relies on low-cost primary assays to prioritize compounds for more expensive dose-response profiling, where potency is ul

Private and interpretable clinical prediction with quantum-inspired tensor train models

arXiv:2602.06110v2 Announce Type: replace Abstract: Publicly available clinical machine learning models pose an underappreciated privacy risk: their parameters or outputs can be exploited to recover i

pro-team at LLMs4OL 2026 Tasks Flagship and Reuse: Retrieval-Augmented Generation and Vocabulary-Constrained Filtering for Ontology Learning

arXiv:2608.27101v1 Announce Type: new Abstract: Ontology learning from text remains challenging despite significant progress in Large Language Models (LLMs), which can hallucinate domain terms, produc

ProofEvolve: Neuro-Symbolic Evolution for Formal Automated Theorem Proving

arXiv:2608.26334v1 Announce Type: new Abstract: Automated theorem proving offers a natural foundation for recursive self-improvement in scientific discovery. However, existing neural provers do not fu

Property-Specific Recoverability from Contact PPG to Camera rPPG under Heterogeneous Observation Conditions

arXiv:2608.27392v1 Announce Type: cross Abstract: Camera-derived remote photoplethysmography (rPPG) is commonly validated through endpoint accuracy, but endpoint performance does not establish whether

Provable one-poison backdoor attacks on linear models and ReLU neural networks

arXiv:2508.05600v3 Announce Type: replace Abstract: Backdoor poisoning attacks are a threat to machine learning models that are trained on data collected from untrusted sources; these attacks enable a

Real-time virtual circuits for plasma shape control via neural network emulators: integration and testing in the MAST-U PCS

arXiv:2608.26216v1 Announce Type: cross Abstract: The deployment of advanced, AI-enabled control algorithms in tokamak experiments requires robust integration with existing plasma control system (PCS)

Reasoning about In-Context Samples for Machine-Translation

arXiv:2608.27036v1 Announce Type: new Abstract: Large Language Models (LLMs) can be trained to perform chain-of-thoughts reasoning in order to improve the reliability of their responses. In this work,

RECAP-Forcing: Retaining Content Appearances for Long Video Generation

arXiv:2608.26671v1 Announce Type: new Abstract: Long autoregressive video generation faces a fundamental memory challenge: with a finite attention window, a model must decide which information from an

Recipes for Steering and Scaling LLMs via Sampling

arXiv:2608.26120v1 Announce Type: new Abstract: Large Language Models (LLMs) are probabilistic models, typically defined by an autoregressive factorization. While recent work has begun to study richer

Reconstructing Humans and Objects in Interaction using Large Reconstruction Models

arXiv:2608.27407v1 Announce Type: new Abstract: Estimation of Human-Object Interactions in 3D (3D HOI) is a fundamental problem in 3D computer vision with applications in AR/VR, robotics, and embodied

Recurrent Reinforcement Learning with Memoroids

arXiv:2402.09900v4 Announce Type: replace-cross Abstract: Memory models such as Recurrent Neural Networks (RNNs) and Transformers address Partially Observable Markov Decision Processes (POMDPs) by map

Relational Over-Regularization: Graph-Based AI-Generated Text Detection via Sentence Transition Deviation

arXiv:2608.26694v1 Announce Type: new Abstract: Detecting AI-generated text (AIGT) remains challenging because existing approaches rely on token-level statistical signals or independent stylometric fe

Relaxation-Aware Multimodal Sensing of Soft Gripper Driven by Structure-Perception-Learning

arXiv:2608.26622v1 Announce Type: new Abstract: Achieving stable, sustained grasping with soft robotic hands remains a fundamental challenge. Compliance enables safe and adaptive contact, yet the intr

Representation Measurements Under Function-Preserving Reparameterizations

arXiv:2608.27020v1 Announce Type: cross Abstract: Hidden coordinates are not uniquely determined by a language model's input--output function, so representation-derived measurements should be invarian

Representing and Parsing Korean Constituency Structure at Different Levels of Granularity

arXiv:2608.27035v1 Announce Type: new Abstract: Korean constituency parsing raises a representational challenge because the terminal units of a phrase-structure tree do not straightforwardly correspon

Model Releases

Rethinking Image Processing for the Age of AI: A Problem-First Framework for Scientific Progress

model-releasesarxiv-cs-cv

arXiv:2608.26833v1 Announce Type: new Abstract: Modern AI has greatly expanded the capabilities of image processing. However, the ready availability of powerful models, public datasets, and benchmark

Rethinking Message Passing as Retrieval for Text-Attributed Graph Learning

arXiv:2608.26732v1 Announce Type: cross Abstract: Graph neural networks (GNNs) are typically conceptualized as message-passing neural networks, yet it remains unclear why neighborhood aggregation reli

Ring Forcing: Towards Precise Long-Term Memory for Autoregressive Video Diffusion

arXiv:2608.26794v1 Announce Type: new Abstract: Scaling video generation to long durations reveals a critical bottleneck: current models lack robust long-term memory. This deficiency can be studied al

Robust Neural Stimulation Response Modeling Through Meta-Learning and Pretraining

arXiv:2608.26649v1 Announce Type: new Abstract: Objective: Model-based closed-loop neural stimulation holds promise for therapeutic applications ranging from Parkinson's disease to sensory restoration

RubricRM: Generative Reward Modeling via Dynamic Rubrics for Image Generation and Editing

arXiv:2608.26956v1 Announce Type: new Abstract: Reward models play an essential role in aligning visual generative models, yet most existing visual reward models use a single scalar score or rely on f

SAREF-based Ontology for Distributed AI Workflows across the Edge-Fog-Cloud Continuum

arXiv:2608.26160v1 Announce Type: new Abstract: Nowadays semantic models provide limited support for representing distributed AI workflows and their execution across heterogeneous edge, fog, and cloud

Scaling Model-Generated Distillation Data Can Make Latent Teacher Traits More Recoverable

arXiv:2608.26958v1 Announce Type: cross Abstract: Scaling model-generated data is usually viewed as improving distillation: more examples should increase coverage, reduce noise, and produce stronger s

Scaling phoneme-based TTS augmentation for ASR: A unified pipeline and controlled study

arXiv:2608.26697v1 Announce Type: new Abstract: Synthetic speech provides scalable supervision for automatic speech recognition (ASR), but its benefit depends on the selected texts, reference speech,

SCIT: Testing Causal Cache Carriers in Latent Chain-of-Thought Models

arXiv:2608.27265v1 Announce Type: new Abstract: Latent chain-of-thought models move intermediate reasoning from emitted text into continuous states, improving compactness but hiding the causal object.

Self-Augmented Diffusion Guidance for Physics-Informed Generation

arXiv:2608.26748v1 Announce Type: new Abstract: Diffusion models can be used to generate spatiotemporal signals of physical phenomena, such as time-series images of fluid dynamics. However, a major li

Sequential Additivity in Distributionally Robust Ranking and Selection

arXiv:2509.06147v2 Announce Type: replace-cross Abstract: Ranking and selection (R&S) seeks to identify the alternative with the best mean performance from a finite collection of simulated alternative

Simple Actors and Deep Critics for Scalable Reinforcement Learning

arXiv:2608.26659v1 Announce Type: new Abstract: Recent progress in offline reinforcement learning (RL) has been driven by expressive generative actors such as diffusion and flow-matching policies, whi

Soft Active Electromyography Interface for Machine Learning-Enabled Silent Speech Recognition

arXiv:2608.27048v1 Announce Type: new Abstract: Silent speech recognition (SSR) provides an alternative communication pathway in the absence of audible speech. However, conventional approaches are lim

SPAR-K: Scheduled Periodic Alternating Early Exit for Spoken Language Models

arXiv:2603.09215v2 Announce Type: replace Abstract: Interleaved spoken language models (SLMs) alternately generate text and speech tokens, but decoding at full transformer depth for every step becomes

Stageboost: Recommending Signals Based on Counterfactual Estimation

arXiv:2608.27366v1 Announce Type: cross Abstract: Signals are short textual or visual snippets displayed on the eBay View-Item (VI) page, providing additional, contextual information for users about t

STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

arXiv:2608.27225v1 Announce Type: cross Abstract: Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing work

Structured Evidence Routing for Incident Risk Prediction from Multimodal Longitudinal EHRs

arXiv:2608.26191v1 Announce Type: new Abstract: Incident risk prediction from longitudinal electronic health records (EHRs) is challenging because relevant signals are multimodal, weak in isolation, a

Survival-Guided Length Control for Efficient Diffusion Language Models

arXiv:2608.26374v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text by iteratively denoising masked sequences, but standard decoding either fixes the sequence length or reli

Sycophancy Suppression Can Impair Rational Updating: Anti-Sycophancy Should Preserve the Ability to Update

arXiv:2608.26511v1 Announce Type: new Abstract: Large language models often exhibit sycophancy, revising their answers to align with users when users push back. Such answer flips, however, can arise f

SymbolLKG: Towards Verifiable Logical Reasoning via Logical Knowledge Graph and Symbolic Solvers

arXiv:2608.26836v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language understanding, yet they struggle with strict multi-step reason

Tabular Deep Learning for Algorithmic Trading: Cross-Regime Bayesian Optimisation for Equity Signal Generation

arXiv:2608.27076v1 Announce Type: new Abstract: Algorithmic trading now represents a market exceeding $20 billion, where even marginal gains in signal robustness can translate into economically signif

Task-space model-based control of pneumatic soft actuators

arXiv:2608.27186v1 Announce Type: new Abstract: Soft actuators enable dexterous and compliant interaction, but closed-loop task-space control remains challenging due to strong nonlinearities, distribu

Technical Comparative Benchmarking Study: Advanced AI Hybrid Methods for Renewable Energy Farm Optimization and Forecasting

arXiv:2608.26613v1 Announce Type: new Abstract: This study provides a comprehensive benchmarking of conventional machine learning (ML), ensemble learning, deep neural networks, recurrent architectures

Temporal Sensitivity Analysis of Tessera Embeddings

arXiv:2608.27175v1 Announce Type: new Abstract: Many Earth Observation applications need land-use/land-cover maps that are both precise and frequently updated, yet the strongest Earth Observation foun

TemporalFlow-VLA: Learning Physically Grounded Execution History for Long-Horizon Robot Manipulation

arXiv:2608.26821v1 Announce Type: new Abstract: Vision-language-action (VLA) models leverage pretrained vision-language representations for robot control, yet simply adding historical frames does not