research

MusiChat: Vibe Composing for Music Creation

arXiv:2607.24873v1 Announce Type: new Abstract: Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts. However, most existing system

MyMentorLLM: A psychotherapy GenAI environment with multimodal voice/text patients, trainees and experts for deliberate practice

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arXiv:2607.25667v1 Announce Type: cross Abstract: Psychotherapists need repeated training and supervision by experts; however, scalability is problematic. Here we present MyMentorLLM, a multimodal voi

researcharxiv-cs-ai

29 Jul 2026

Neural Network Learning of One-Bit Protocols for Qubit Measurement Simulation

arXiv:2607.23645v1 Announce Type: cross Abstract: Communication complexity provides a natural framework for quantifying the classical resources required to reproduce quantum statistics. In the qubit p

Nudging Sustainable Choices through LLM-Generated Recommendation Explanations

arXiv:2607.25726v1 Announce Type: new Abstract: Recommender systems mediate everyday consumption, offering a promising channel for encouraging sustainable choices. Prior research shows that explanatio

Observing sycophantic AI validate others reduces its appeal but not its persuasiveness

arXiv:2607.25166v1 Announce Type: new Abstract: AI chatbots can be ``sycophantic,'' or overly agreeable and flattering toward users. Sycophantic AI has been shown to entrench attitudes, yet users freq

OmniQEC: discovering practical quantum error-correcting codes by an AI scientist

arXiv:2607.25865v1 Announce Type: cross Abstract: Quantum error correction (QEC) is indispensable for scalable fault-tolerant quantum computing. However, discovering QEC codes that remain effective is

Online learning of subgrid-scale models for quasi-geostrophic turbulence in planetary interiors

arXiv:2511.14581v2 Announce Type: replace-cross Abstract: Machine learning approaches to subgrid-scale (SGS) modelling are now well established in atmospheric and oceanic applications. Among these, on

Open-Ended CT Volume Segmentation with Weak Supervision from Language

arXiv:2607.25860v1 Announce Type: new Abstract: We introduce a method for training a text-conditioned segmentation model for CT scans, which combines voxel-level supervision with coarse but scalable s

Optimal Ansatz-free Hamiltonian Learning In Situ

arXiv:2606.19486v2 Announce Type: replace-cross Abstract: Characterizing the features of a Hamiltonian that governs a quantum system serves as a fundamental subroutine of quantum device calibration, s

Optimization with Dynamic Constraint Learning (DCL)

arXiv:2607.25719v1 Announce Type: new Abstract: We propose Dynamic Constraint Learning (DCL), a data-driven framework for constrained optimization when constraint functions are unknown and cannot be q

OrganLens: Organ-Specific Representation Learning for CT Foundation Models

arXiv:2607.25164v1 Announce Type: cross Abstract: A CT examination captures multiple organs, but many biomedical questions concern abnormalities, prognosis, or longitudinal change in a specific organ.

Physics-Informed Broad Learning System: An Efficient Backpropagation-Free Framework for Solving Partial Differential Equations

arXiv:2607.25608v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs) by embedding governing

Physics-Informed Neural Operator for Warm-Starting Background-Decomposed and Preconditioned PSFD: Enabling Scalable 3-D EUV Mask Simulation

arXiv:2607.25330v1 Announce Type: cross Abstract: We present a physics-informed neural operator (PINO) trained with pseudo-spectral frequency-domain (PSFD) equations for electromagnetic (EM) scatterin

PreDiff-LM: Pretrained Discrete Masked Diffusion Language Modeling with Hybrid Attention

arXiv:2607.25157v1 Announce Type: new Abstract: Discrete masked diffusion language models support bidirectional generation and infilling, but adapting pretrained autoregressive (AR) transformers requi

Prototype Adaptation for Zero-Shot sEMG Movement Classification

arXiv:2607.25826v1 Announce Type: new Abstract: Surface electromyography (sEMG) enables the control of prostheses, allowing upper-limb amputees to re-gain some hand function. Most current research foc

Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Being

arXiv:2607.25057v1 Announce Type: new Abstract: As conversational AI systems become increasingly integrated into daily life, their potential effects on user well-being require ongoing attention. While

Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise

arXiv:2607.25492v1 Announce Type: new Abstract: We study stochastic optimization with heavy-tailed gradient noise. We first propose a novel quantum mean estimator for multivariate heavy-tailed random

Raven: High-Recall Sequence Modeling with Sparse Memory Routing

arXiv:2607.25357v1 Announce Type: cross Abstract: Long-context recall in linear-time sequence models highlights a tradeoff in how they write to memory. State-based linear models, such as state-space m

Re-thinking Mammography Transfer Learning: The Dataset-Informed Transfer Learning (DITL) Framework for Breast Cancer Screening and Lesion Diagnosis

arXiv:2607.26043v1 Announce Type: new Abstract: Enhancing classification performance in mammography remains a persistent challenge across both small curated datasets and large-scale clinical cohorts.

Reading Legends on Ancient Coins: An Object Detection Approach for Character Recognition on a Novel Roman Republican Dataset

arXiv:2607.25455v1 Announce Type: new Abstract: When it comes to the proper classification of ancient coins with respect to their time and issuer, the textual inscriptions on these coins, also known a

Real-time Spatial Retrieval Augmented Generation for Urban Environments

arXiv:2505.02271v2 Announce Type: replace Abstract: The proliferation of Generative Artificial Ingelligence (AI), especially Large Language Models, presents transformative opportunities for urban appl

Retrieval, not hallucinations, will be the limiting factor for LLM-based clinical AI tools

arXiv:2607.24793v1 Announce Type: cross Abstract: Discussions around large language model (LLM) errors in clinical artificial intelligence (AI) generally center around precision errors like hallucinat

researcharxiv-cs-cl

Right-sizing Recommendations (RSR): Cloud Workload Conformal Prediction for Virtual Machines in Data Center Operations

arXiv:2607.24773v1 Announce Type: new Abstract: Managing cloud infrastructure efficiently, especially in environments of large cloud providers or hyperscalers, requires optimizing the use of physical

RoCo-ACE: Rollout-Conditioned Online Distillation for Retention-Aware Knowledge Injection

arXiv:2607.24771v1 Announce Type: new Abstract: Knowledge injection updates pretrained MLLMs with new factual or domain-specific knowledge, but fitting full authoritative answers can cause drift in no

Room-Mediated Co-occurrence for Zero-Shot Object-Centric Semantic Navigation via Frontier Scoring

arXiv:2607.25448v1 Announce Type: new Abstract: Zero-shot ObjectNav methods increasingly use vision-language priors, but direct object-object similarity in the latent space is often a weak proxy for s

researcharxiv-cs-ro

Salient Knowledge Pathways: Sparse Cross-Modal Routing for Efficient Knowledge-Intensive Multimodal Question Answering

arXiv:2607.25422v1 Announce Type: new Abstract: Knowledge-intensive multimodal question answering (KI-MMQA) sits at the intersection of three expensive primitives: long visual token sequences, dense r

ScalableRAG: High-Quality RAG at Zero Ingestion Cost

arXiv:2607.25135v1 Announce Type: new Abstract: Recent advances in RAG aim to optimize for performance by paying high ingestion costs for knowledge ingestion: building knowledge graphs or extracting S

Schrodinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics

arXiv:2607.25984v1 Announce Type: new Abstract: Predicting how a scene may evolve from partial observations requires reasoning about multiple possible futures rather than committing to a single trajec

SciClaimSeekers at CheckThat! 2026: Retrieving Scientific Sources for Social Media Claims with LLM Reranking

arXiv:2607.24803v1 Announce Type: cross Abstract: Scientific claims often spread on social media faster than they can be verified, while posts rarely link to the original scholarly sources. To tackle

researcharxiv-cs-cl

Score-Based Stabilization for Time-Dependent Problems

arXiv:2607.25119v1 Announce Type: new Abstract: We propose a score-based stabilization framework for numerical simulation of partial differential equations, in which a learned score model defines a st

Seen, Said, or Forgotten? A Causal Audit of Visual KV Memory Across Dialog Turns

arXiv:2607.25467v1 Announce Type: cross Abstract: Stateful multimodal assistants encode an image once but may answer questions about it many turns later. Attention-guided visual-KV eviction assumes th

Selective Impairment of Motor Recovery from Typing Errors in Parkinson's Disease: A Survival Analysis

arXiv:2607.24796v1 Announce Type: cross Abstract: Parkinson's disease (PD) affects multiple, dissociable stages of motor and cognitive control. We ask whether passively-collected keystroke dynamics ca

Semantic Space Search Trajectory Networks

arXiv:2607.25122v1 Announce Type: new Abstract: Search Trajectory Networks (STNs) are a graph-based tool for visualizing and characterizing the behavior of optimization algorithms. STNs' reliance on d

SepPrune:A Separator-based Pruning Framework for Efficient Multimodal Large Language Models

arXiv:2607.25818v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs), such as Qwen2.5-VL and InternVL3, generate large numbers of vision tokens for high-resolution inputs, l

Sheet As Token: A Graph-Enhanced Representation for Multi-Sheet Spreadsheet Understanding

arXiv:2605.05811v2 Announce Type: replace Abstract: Workbook-scale spreadsheet understanding is increasingly important for language-model-based data analysis agents, but remains challenging because re

Stable FP4 Training via Transposition-Invariant Block Quantization

arXiv:2607.24953v1 Announce Type: cross Abstract: Reducing training precision is a key lever for improving the e ciency of large language model (LLM) training, but pushing beyond FP8 to 4-bit oating p

Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with C^{s,lambda} Targets

arXiv:2602.20555v2 Announce Type: replace-cross Abstract: The tremendous success of Transformer models in fields such as large language models and computer vision necessitates a rigorous theoretical i

Steering topology distributions for unified generative design of architected metamaterials

arXiv:2607.24777v1 Announce Type: new Abstract: Architected metamaterials derive their functions from structure, creating vast opportunities to program physical responses through topology design. Howe

Stemma: Induced Decision Regions Reveal LLM Provenance

arXiv:2607.25880v1 Announce Type: cross Abstract: LLM provenance testing asks whether a suspect LLM belongs to the same lineage as a source. Existing black-box methods largely infer this relationship

Stronger Memory-Query Tradeoffs for Convex Optimization: The Limitations of Subquadratic Memory

arXiv:2607.24827v1 Announce Type: cross Abstract: We prove two lower bounds for the first order oracle complexity of minimizing a d-dimensional 1-Lipschitz convex function over the unit ball with m bi

The Effect of Text Chunk Size on Retrieval-Augmented Generation Performance

arXiv:2607.24767v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems have emerged as a powerful process for allowing large language models (LLMs) to retrieve relevant informa

TIGA: Trajectory-Injected Generative Attack against Black-box AIGC Detectors

arXiv:2607.25894v1 Announce Type: new Abstract: Recent diffusion models have achieved remarkable realism in facial image synthesis, posing growing challenges to artificial intelligence-generated conte

Toward a systematic method for identifying language areas

arXiv:2607.25305v1 Announce Type: new Abstract: Macroareas are geographical areas used in typological research for grouping variables of interest. In linguistic typology, languages in a given macroare

researcharxiv-cs-cl

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories

arXiv:2412.18756v2 Announce Type: replace Abstract: A primary advantage of neural networks lies in their feature learning characteristics, which is challenging to theoretically analyze due to the comp

Towards real-time surrogate-free Bayesian inversion for neutron reflectometry

arXiv:2509.06924v3 Announce Type: replace Abstract: Neutron reflectometry (NR) is a key enabling technology for many areas of scientific development. Although the forward reflectivity model is well-kn

Towards Reliable Stain Transfer: An Iterative Data-Model Co-Optimization Framework Based on Multimodal Expert-Guided Assessment

arXiv:2607.25393v1 Announce Type: new Abstract: Histopathological examination primarily relies on hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining. Although IHC provides critical mo

Transformer Transformer: A Unified Model for Motion-Conditioned Robot Co-design

arXiv:2607.25798v1 Announce Type: new Abstract: An often overlooked factor of robot manipulation performance is the embodiment of the robot itself. Motivated by this problem, we study motion-condition

researcharxiv-cs-ro

TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation

arXiv:2607.25471v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) and Large Language Models (LLMs) have each advanced recommendation systems by modeling structural and semantic signals, res