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Brilliant new paper from Meta. LLM judges get validated on accuracy against golden data. That says nothing about whether the verdict survive…

Brilliant new paper from Meta. LLM judges get validated on accuracy against golden data. That says nothing about whether the verdict survives when questioned. The Wiggle Framework stress-tests 9 front

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Can Generalist Vision Language Models (VLMs) Rival Specialist Medical VLMs? Benchmarking and Strategic Insights

DGX agent

arXiv:2506.17337v5 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have shown promise in automating image diagnosis and interpretation in clinical settings. However, developing sp

researcharxiv-cs-ai

14 Aug 2026

Can Spectral-Clipping Enable Better Learning While Forgetting Less for Low-Rank Adaptation?

arXiv:2608.12332v1 Announce Type: new Abstract: In recent years, low-rank adaptation (LoRA) has emerged as a significant paradigm that freezes pre-trained weights and introduces small, learnable adapt

researcharxiv-cs-cl

CAPRI: Contract-Aware Proof Repair for Isabelle

arXiv:2608.13459v1 Announce Type: cross Abstract: We address the use of large language models (LLMs) to help discover Isabelle proofs. An Isabelle build establishes that the submitted theory is accept

Capstan-driven Continuum Surgical Robot: Design, Modeling, and Perception

arXiv:2608.13396v1 Announce Type: new Abstract: Shape and force sensing have long been critical bottlenecks in the development of compact capstan-driven continuum surgical robots, primarily due to the

Comment on 'Modeling rapid language learning by distilling Bayesian priors into artificial neural networks'

arXiv:2608.12974v1 Announce Type: cross Abstract: McCoy & Griffiths (2025, henceforth M&G) suggest that a Bayesian prior can be distilled into Artificial Neural Networks (ANNs) through Model-Agnostic

researcharxiv-cs-cl

Communication Heterogeneity and Collective Consensus in Neural Cellular Automata

arXiv:2606.21202v2 Announce Type: replace-cross Abstract: Reaching global agreement from purely local interactions is a defining problem of collective intelligence, and most models of it assume that a

Concept Drift Detection and Adaptive Retraining of Malware Classification Models

arXiv:2608.13465v1 Announce Type: cross Abstract: Concept drift refers to changes over time in the statistical properties of data, as compared to the data that was used to train a learning model. Mach

Confidence-Calibrating Regularization for Robust Brain MRI Segmentation Under Domain Shift

arXiv:2509.23176v2 Announce Type: replace Abstract: The Segment Anything Model (SAM) exhibits strong zero-shot performance on natural images but suffers from domain shift and overconfidence when appli

CoverPrune: Coverage-Driven Token Pruning for 3D VLMs via Optimal Transport

arXiv:2608.13226v1 Announce Type: cross Abstract: While 3D Vision-Language Models (3D VLMs) have demonstrated remarkable spatial reasoning capabilities, they suffer from massive visual token counts th

DARTree: Speculative Diffusion Decoding with Autoregressive Draft Trees

arXiv:2608.13524v1 Announce Type: new Abstract: Speculative decoding losslessly accelerates autoregressive language models by verifying multiple draft tokens in parallel. Diffusion-based drafters furt

Dead text or binding clause? Measuring and restoring constraint influence in black-box LLM dialogues

arXiv:2608.12599v1 Announce Type: new Abstract: Multi-turn dialogues let users revoke constraints as easily as impose them, but revocation does not reliably take effect: models keep enacting withdrawn

Decomposition of Evidence, Contradiction, and Fragility in Perturbation Responses

arXiv:2608.12935v1 Announce Type: new Abstract: Perturbation methods explain model decisions by measuring prediction changes under altered inputs, but response magnitude tells us only how much a model

Defensive Boosting for Online Probabilistic Forecasting

arXiv:2608.13554v1 Announce Type: new Abstract: We study online probabilistic forecasting of binary outcomes chosen by an adaptive adversary. Given an online learning algorithm for a weak hypothesis c

Demand Transfer Estimation at Scale via Restricted Logit Modeling

arXiv:2608.12680v1 Announce Type: cross Abstract: Item demand forecasting is an integral component of store assortment optimization. Existing literature focuses on learning a suitable customer choice

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming

arXiv:2608.12757v1 Announce Type: cross Abstract: Laplacian-regularized minimization is fundamental in signal processing and machine learning, but is limited by the dense and ill-conditioned nature of

Distribution Steering via Sliced Optimal Transport Control

arXiv:2608.12828v1 Announce Type: cross Abstract: Distribution steering seeks feedback laws that drive the state law of a dynamical system between prescribed initial and terminal distributions. Optima

DMDIntel: Interpreting Large Language Models via Dynamic Mode Decomposition

arXiv:2608.13048v1 Announce Type: new Abstract: In this work, we introduce DMDIntel which uses dynamic mode decomposition (DMD) to make the predictions made by LLMs in a classification task interpreta

DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation

arXiv:2608.13489v1 Announce Type: new Abstract: We present extbf{DreamX-Phi 1.0}, an action-conditioned video world model for robotic manipulation that, given an observed frame, a language instruction

Dual-Flow Transformers: Decoupling the Primary Prefill Path from Additional Decode Computation

arXiv:2608.12385v1 Announce Type: new Abstract: As large language models serve more requests, cumulative inference cost is becoming increasingly important relative to one-time training cost. The two i

DYSANOS Generative Dynamic Smooth Arbitrage-free Non-parametric Option Surfaces

arXiv:2608.12587v1 Announce Type: cross Abstract: This article presents with DYSANOS the first generative market model for smooth SANOS option surfaces for all strikes and expiries which are free of s

EEG-PRIME: Prototype-Aligned Representation Learning with Multi-Level Conditioning for EEG Decoding

arXiv:2608.13072v1 Announce Type: new Abstract: Electroencephalography (EEG) decoding models often generalize poorly across datasets and subjects due to domain shifts in acquisition protocols and indi

Efficient Hessian-Free Methods for Multi-Objective Bilevel Optimization with Nonconvex Lower Level

arXiv:2608.12704v1 Announce Type: cross Abstract: Multi-objective bilevel optimization has wide applications in the AI area such as automated learning and multi-task meta-learning. Although recently s

Efficient Image Restoration with State-Dependent Forward Diffusion

arXiv:2505.16733v3 Announce Type: replace Abstract: This paper proposes to perform image restoration through a state-dependent mean-reverting forward diffusion (FoD) process. In contrast to traditiona

Enhancing In-Hospital Mortality Prediction Using Multi-Representational Learning with LLM-Generated Expert Summaries

arXiv:2411.16818v2 Announce Type: replace-cross Abstract: To evaluate a multi-representational framework in which large language model (LLM)-generated expert summaries of intensive care unit (ICU) not

Equivariant learning of a transferable three-dimensional classical density functional

arXiv:2608.13506v1 Announce Type: cross Abstract: Liquids exhibit collective behavior that depends sensitively on thermodynamic conditions, interfaces and confinement, yet predicting each new state co

Evolutionary Brain-Body Co-Optimization Consistently Fails to Select for Morphological Potential

arXiv:2508.17464v2 Announce Type: replace Abstract: Brain-body co-optimization remains a challenging problem. To understand and overcome its challenges, we exhaustively map a morphology-fitness landsc

Excitation-Supervised Closed-Loop Self-Calibration and Target Seeking for an Unknown-Pose Range-Bearing Relay

arXiv:2608.12528v1 Announce Type: cross Abstract: A vehicle seeking a hidden target through a range-bearing relay of unknown position and yaw must decide, online, whether its own motion has already ma

Exemplar-based objective classification of gust-induced loads across multiple flight conditions

arXiv:2608.12448v1 Announce Type: new Abstract: Is it possible to find an objective classification criterion that organizes the complexity of gust-induced loads across many flight conditions? And one

Exploiting Symbolic Heuristics for the Synthesis of Domain-Specific Temporal Planning Guidance using Reinforcement Learning

arXiv:2505.13372v2 Announce Type: replace Abstract: Recent work investigated the use of Reinforcement Learning (RL) for the synthesis of heuristic guidance to improve the performance of temporal plann

Exploring Instruction Data Quality for Explainable Image Quality Assessment

arXiv:2510.03880v2 Announce Type: replace Abstract: In recent years, with the rapid development of large multimodal models (LMMs), explainable image quality assessment (IQA) has attracted increasing a

Exploring Oversmoothing with Householder Matrices

arXiv:2608.12514v1 Announce Type: new Abstract: Deep graph neural networks(GNNs) suffer from oversmoothing- a progressive collapse of node representation towards a low information subspace as network

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure

arXiv:2608.13549v1 Announce Type: new Abstract: The per-instance Jaccard score, or intersection over union (IoU), is standard in multi-label classification and binary segmentation. With s labels, its

FAM-DQ: A Dual-Quadrotor-Based Fully Actuated Aerial Manipulator for High-Torque Interaction

arXiv:2608.13220v1 Announce Type: new Abstract: Aerial physical interaction requires aerial manipulation platforms to generate large interaction forces and torques while maintaining precise end-effect

Fast Iterative Five point Relative Pose Estimation

arXiv:2608.13114v1 Announce Type: new Abstract: Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point

Fast Length-Squared Sampling for Positive-Semidefinite Matrices

arXiv:2608.12503v1 Announce Type: cross Abstract: We describe a simple rejection-sampling-based algorithm to perform length-squared sampling on an n imes n positive-semidefinite (psd) matrix: that is,

Federated Compositional Muon Optimizer for Matrix-Wise Models

arXiv:2608.12710v1 Announce Type: new Abstract: Muon, a more recently developed optimizer, is useful for matrix-wise models in AI areas. Although many works have studied Muon and its variants, these m

Fidelity-Constrained Anchoring for Black-Box Denoisers

arXiv:2608.13194v1 Announce Type: new Abstract: We propose a fidelity-constrained framework that anchors the output of a black-box denoiser to its input without retraining and with little additional c

Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization

arXiv:2608.12687v1 Announce Type: new Abstract: Bayesian optimization (BO) is a sample-efficient framework for analog circuit topology search, where evaluating each candidate topology can require cost

Fine-Grained Action Recognition with Cross-Attentive Latent Sparse Experts

arXiv:2608.13458v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) must distinguish visually similar actions that differ mainly in body configuration, timing, or local appear

Fine-tuned Normalizing Flows for ALICE Zero Degree Calorimeter Fast Simulation

arXiv:2608.12795v1 Announce Type: cross Abstract: Simulating the ALICE Zero Degree Calorimeter (ZDC) neutron detector responses at the LHC is computationally expensive, requiring complex Monte Carlo c

Foundations of Independent Component Analysis

arXiv:2608.13229v1 Announce Type: cross Abstract: We present the mathematical foundations of linear independent component analysis (ICA) models based on standard literature in a self-contained note. I

Foundations of MT-PDCL: Measure-Theoretic Probabilistic Definite Clause Logic

arXiv:2608.13018v1 Announce Type: new Abstract: Standard probabilistic logic programming frameworks typically rely on grounding logic programs into discrete propositional representations. This operati

From Approximation Rates to Loss-Landscape Barrier Decay in Shallow ReLU Networks

arXiv:2602.17596v2 Announce Type: replace Abstract: We study pathwise connectivity of sublevel sets for one-hidden-layer ReLU networks with constrained first-layer weights and an ell_1 penalty on the

From Observation to Intervention: Memory in Brains and Large Language Models

arXiv:2608.12377v1 Announce Type: cross Abstract: Brains and large language models (LLMs) are fundamentally different memory systems, but they can be compared through shared functional questions: wher

From Refuse to Richness: Rubric Rewards for Long-Form Hallucination Reinforcement Learning

arXiv:2608.12337v1 Announce Type: new Abstract: Rewards that penalize unsupported claims can improve grounding in long-form generation, but they can also teach models to answer less. We study this ref

researcharxiv-cs-cl

Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces

arXiv:2511.06239v2 Announce Type: replace-cross Abstract: Learning-based methods for sampling from the Gibbs distribution in finite-dimensional spaces have progressed quickly, yet theory and algorithm

GEM: A Generative Embedding Model Bridging Reasoning and Retrieval

arXiv:2608.13200v1 Announce Type: cross Abstract: Modern LLMs excel at reasoning and instruction following, enabling users to express complex and diverse information needs. However, conventional retri