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VINCENT: Validated Interaction Network for Cross-drug Explanation of Therapeutics

arXiv:2608.25841v1 Announce Type: new Abstract: Drug synergy prediction estimates whether two drugs produce a stronger joint effect than expected from their individual activities. For drug combination

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Virgil: Navigating Explainability for Transformer-based Language Models

DGX agent

arXiv:2608.25555v1 Announce Type: new Abstract: Explainability for transformer-based language models is becoming crucial as these systems are deployed in high-stakes applications. As a result, the eco

researcharxiv-cs-cl

27 Aug 2026

Visual General Intelligence: A White Paper

arXiv:2608.25924v1 Announce Type: new Abstract: This paper reconsiders intelligence from a vision-centered perspective and examines whether intelligence emerging from visual experience and learning ma

What Do Audio-Visual Synchronization Metrics Actually Measure?

arXiv:2608.25157v1 Announce Type: new Abstract: Automatic AV-sync metrics are widely used to rank and train audio-visual generators, but they are rarely audited as measurement instruments. We jointly

When Composition Doesn't Add Up: Humans Identifying Defects in AI-Generated Images

arXiv:2608.25933v1 Announce Type: new Abstract: *Chulin Zhao and Ruoqi Hu contributed equally to this work. State-of-the-art text-to-image (T2I) models exhibit pronounced and systematic defects when p

When Personality Meets Quantization: A Layer-wise MBTI Analysis of Quantized LLMs

arXiv:2608.25977v1 Announce Type: new Abstract: Personality is increasingly important in large language models (LLMs), as it shapes users' trust, engagement, and emotional experiences. While the Myers

researcharxiv-cs-cl

When Pruning Meets Interpretability: Preserving Sparse Autoencoder Robustness in LLMs

arXiv:2608.25941v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are widely used to interpret the internal representations of large language models (LLMs), yet their reliability under post-h

Why ML-based cough models do not generalize: a systematic cross-dataset evaluation for tuberculosis screening

arXiv:2608.25846v1 Announce Type: cross Abstract: Cough acoustics are promising for non-invasive tuberculosis (TB) screening, yet whether machine learning (ML) models capture disease-related acoustics

A Data-dependent Early Stopping Rule using Rademacher Complexity with L1-norm

arXiv:2608.24210v1 Announce Type: new Abstract: Training neural networks requires balancing the trade-off between fitting the training data and achieving robust performance on unseen inputs. This abil

A Discriminative Latent-Variable Model for Bilingual Lexicon Induction

arXiv:1808.09334v4 Announce Type: replace-cross Abstract: We introduce a novel discriminative latent variable model for bilingual lexicon induction. Our model combines the bipartite matching dictionar

A Durable Vision-Based Tactile Fingertip for Robotic Manipulation

arXiv:2608.24242v1 Announce Type: new Abstract: Currently available commercial vision-based tactile sensors provide rich contact information but remain vulnerable to abrasion and repeated concentrated

A Formal Methodological Framework for Auditing Robustness and Fidelity in Explainable AI: From Application to Trust Certification

arXiv:2608.23817v1 Announce Type: new Abstract: SHAP and LIME are now standard tools for interpreting black-box predictions, yet their outputs can vary substantially when the input is perturbed by sma

A Judge Should Know What Changed:Construct Validity for LLM-as-a-Judge Evaluation

arXiv:2608.24419v1 Announce Type: new Abstract: LLM-as-a-judge evaluation is usually assessed by agreement and robustness to surface perturbations, but reliability does not establish construct validit

A Literate Programming Environment for Human and Machine Agents

arXiv:2608.24644v1 Announce Type: cross Abstract: This paper introduces an environment for constructing literate programs in concert with language-aware machine agents. This environment includes a gra

A Mathematical Theory of Interpretation: Rational Entropy, Spectral Readout, and Confusability as a Resource

arXiv:2608.23892v1 Announce Type: cross Abstract: This article presents the abridged core of A Mathematical Theory of Interpretation (MTI), which treats interpretation as observer-relative spectral me

A Robust Task-Level Control Architecture for Learned Dynamical Systems

arXiv:2511.09790v2 Announce Type: replace-cross Abstract: Dynamical system (DS)-based learning from demonstration (LfD) is a powerful tool for generating motion plans in the operation ('task') space o

A Structural FHMM for Interpretable Disease Trajectories in T2DM

arXiv:2608.24328v1 Announce Type: new Abstract: In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the analysis of disease trajectories in patients with Type

A survey detection channel overrides the pixels in an astronomical foundation model, and biases tomographic mean redshifts

arXiv:2608.23626v1 Announce Type: new Abstract: Foundation models for astronomy are trained on survey pixels together with the catalogue products derived from those pixels. Those catalogues are incomp

A Theory of Speciation in Generative Diffusion Models on Compact Riemannian Manifolds

arXiv:2608.23798v1 Announce Type: new Abstract: Speciation in generative diffusion models denotes the emergence of distinct stable branches during denoising, through which initially undifferentiated t

Ad Insertion in LLM-Generated Responses

arXiv:2601.19435v2 Announce Type: replace-cross Abstract: Sustainable monetization of large language models (LLMs) remains a critical open challenge. Traditional search advertising, which relies on st

AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods

arXiv:2402.11215v4 Announce Type: replace Abstract: The choice of batch size in minibatch stochastic gradient optimization is critical for both optimization and generalization performance in large-sca

Adaptive Extrapolated Proximal Gradient Methods with Variance Reduction for Composite Nonconvex Finite-Sum Minimization

arXiv:2502.21099v3 Announce Type: replace-cross Abstract: This paper proposes {sf AEPG-SPIDER}, an Adaptive Extrapolated Proximal Gradient (AEPG) method with variance reduction for minimizing composit

AI models flub these intelligence tests. Can you fare any better?

Puzzles and games have been central to AI development since the very beginning. Just as we humans like to test our smarts with crosswords or logic puzzles, developers can test how far models have adva

researchmit-tech-review

Analytical Covariance Propagation for DVL-Aided Loosely Coupled SINS Under Attitude Uncertainty

arXiv:2601.19509v2 Announce Type: replace Abstract: In loosely coupled strapdown inertial navigation system/Doppler velocity log (SINS/DVL) integration, the body-frame DVL velocity is projected into t

AQLoRA: A Zero-Search Recipe for Fast Quantized LoRA Fine-Tuning

arXiv:2608.23816v1 Announce Type: new Abstract: Quantized fine-tuning (QLoRA) saves memory but not time. It dequantizes every 4-bit weight on the fly, so it trains more slowly than fp16 LoRA. We prese

Asymptotically perfect seeded graph matching without edge correlation (and applications to inference)

arXiv:2506.02825v3 Announce Type: replace-cross Abstract: We present the OmniMatch algorithm for seeded multiple graph matching. In the setting of d-dimensional Random Dot Product Graphs (RDPG), we pr

Beauty is in the ELBO of the Beholder: A Variational Account of Processing Fluency in Face Perception

arXiv:2608.24219v1 Announce Type: new Abstract: Facial attractiveness has been linked to statistical regularities such as symmetry and averageness, suggesting that beauty may depend on the ease with w

Beyond Uniform Local Isometry and Topology: FactoMap for Disentangled Representations

arXiv:2608.24762v1 Announce Type: cross Abstract: Many disentanglement methods represent generative factors using Euclidean product coordinates, although the underlying factor spaces may wrap, collaps

Boot-and-Feedback Framework for Generalist-Expert Model Collaboration in Breast Ultrasound Diagnosis

arXiv:2608.23974v1 Announce Type: new Abstract: Breast ultrasound (BUS) is widely used for breast cancer diagnosis yet remains operator-dependent. While deep learning shows promise, ensuring diagnosti

Bridging Teacher Expectations and Robot Learning via Coupling Dynamics

arXiv:2608.23994v1 Announce Type: new Abstract: Human-robot teaching focuses on enabling nontechnical experts to customize robots according to their needs after deployment. With recent advances in mac

Can a Dynamic Internal Field Govern a Transformer's Cognition? Certifiability, not Superiority, in Homeostatic Compute Control

arXiv:2608.24319v1 Announce Type: new Abstract: An intelligent system does not merely reason: it governs its own reasoning - how much to compute, when to stop, which module to activate. Can that role

Can Large Language Models Still Explain Themselves? Investigating the Impact of Quantization on Self-Explanations

arXiv:2601.00282v2 Announce Type: replace-cross Abstract: Quantization is widely used to accelerate inference and streamline the deployment of large language models (LLMs), yet its effects on self-exp

Causal Modelling of Support Interventions for Student Competency Assessment

arXiv:2608.24632v1 Announce Type: new Abstract: Accurate assessment of student competencies is essential for enabling educators to identify individual needs, design targeted interventions, and evaluat

COCI: Conference Organisers and Content Identifier

arXiv:2608.24559v1 Announce Type: cross Abstract: Despite the critical role of grey literature in scholarly communication, artefacts such as Calls for Papers (CfPs) remain largely isolated from modern

Comparative Assessment of Deep Learning Architectures for Underwater Subsurface Kelp Forest Segmentation with The Kelp-o-Tron

arXiv:2608.24594v1 Announce Type: new Abstract: Submerged kelp forests are vital coastal ecosystems that support marine biodiversity and ecosystem dynamics, yet accurate underwater kelp segmentation r

Conditional GraphGANFed: Optimizing Graph-Structured Molecule Generation in Federated Generative Adversarial Networks

arXiv:2608.24610v1 Announce Type: new Abstract: Generative adversarial networks (GANs) have garnered considerable attention in molecular discovery for their ability to generate novel and high-quality

Constrained Hyperparameter Optimization for Streaming Data

arXiv:2608.24712v1 Announce Type: cross Abstract: Optimization of hyperparameters is a critical factor to obtain optimal model performance. While existing research has predominantly concentrated on ba

Contextual Embedding Evidence for Main--Light Verb Distinctions in Urdu

arXiv:2608.23645v1 Announce Type: cross Abstract: Urdu light verbs contribute schematic event-structural meaning while remaining lexically related to corresponding main verbs. This study tests represe

CytoNet: A Foundation Model for the Human Cerebral Cortex at Cellular Resolution

arXiv:2511.01870v3 Announce Type: replace-cross Abstract: Studying the cellular architecture of the human cerebral cortex is essential for understanding how the brain is organized from the micro to th

Decoupling candidate dual AGN from chance superpositions in the GOTHIC survey via a deep-learning framework

arXiv:2608.24164v1 Announce Type: cross Abstract: Dual active galactic nuclei (DAGN) mark a critical phase in the evolution of merging galaxies and the pairing of supermassive black holes, yet they re

Deep Learning Super Resolution for Satellite Cloud Mask Downscaling

arXiv:2608.24715v1 Announce Type: cross Abstract: A vast amount of optical satellite data is being transmitted to Earth-based servers every day, and more than half of this data is affected by haze or

Dimensionless Controls of Plasticity Under Alternating Tasks: From Evolutionary Biology to Continual Learning

arXiv:2608.23889v1 Announce Type: cross Abstract: Plasticity under changing environments is central to both evolutionary biology and continual learning. Motivated by recent work on genotype--phenotype

Disentangled Skill Representations for Predictive Human Modeling

arXiv:2608.23776v1 Announce Type: cross Abstract: Understanding human skill is important for AI systems that collaborate with, coach, or assist people. Unlike typical latent variable estimation proble

Diverse by Reasoning: Harnessing the Wisdom of LLM Crowds for Future Prediction

arXiv:2608.24001v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for future prediction, motivating the use of multiple models as a wisdom-of-the-crowd mechanism. Howe

Do physics-informed neural networks (PINNs) need to be deep? Shallow PINNs using the Levenberg-Marquardt algorithm

arXiv:2602.08515v3 Announce Type: replace-cross Abstract: This work investigates shallow physics-informed neural networks (PINNs) for solving forward and inverse problems governed by nonlinear partial

DreamLedger: Execution-Settled Credit Files for World-Model Imagination in Robot Decision Loops

arXiv:2608.23863v1 Announce Type: new Abstract: Robots are beginning to act on world-model predictions, yet reliability is still expressed through instantaneous, model-internal signals. DreamLedger in

DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection

arXiv:2608.23723v1 Announce Type: new Abstract: Few-shot anomaly detection (FSAD) has recently benefited from vision-language models such as CLIP, which enable anomaly de?tection by aligning visual fe

DRRG: A Discrete Diffusion Framework for Radiology Report Generation

arXiv:2608.24105v1 Announce Type: new Abstract: Purpose: Automatic radiology report generation (RRG) has been widely explored to improve reporting accuracy and reduce radiologists' workload. Most exis