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When the Canonical Completion Is Wrong: Formalizing and Measuring the Jump in Large Language Models

arXiv:2608.26187v1 Announce Type: cross Abstract: Whether large language models (LLMs) can perform the abductive leap from evidence to a new system of axioms, commonly referred to as a jump, has recen

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Which Metrics Save the Most Human Annotation? Prediction-Powered Evaluation and Meta-Evaluation

DGX agent

arXiv:2608.26638v1 Announce Type: new Abstract: Across various non-verifiable tasks, human evaluation is reliable but expensive, while automatic metrics are more scalable but often biased. Building on

researcharxiv-cs-cl

28 Aug 2026

Who Remains, What Changes: Identity Anchored Composed Gait Retrieval

arXiv:2608.26632v1 Announce Type: new Abstract: Gait recognition has achieved remarkable progress, yet existing methods remain confined to rigid visual matching and often overlook the potential of nat

Why Current XAI Is Not Enough for Arabic NLP: A Critical Survey of the Explainability Gap

arXiv:2608.26144v1 Announce Type: new Abstract: Explainable AI (XAI) is now a major theme in NLP; however, Arabic NLP remains under-explained in three connected senses. First, there is a method gap: A

Why not to use the Gaussian kernel

arXiv:2608.26974v1 Announce Type: cross Abstract: Kernels measure similarity or correlation in tasks such as regression and classification. The Gaussian kernel, other names of which include squared ex

Your Voice Cloning System is Secretly a Voice Anonymizer

arXiv:2608.27360v1 Announce Type: new Abstract: Speaker anonymization suppresses speaker-identifying attributes from speech while preserving linguistic content and quality. We propose repurposing XTTS

Zero-Shot Video Restoration and Enhancement with Text-to-Image Latent Diffusion Models and Multi-Modal References

arXiv:2608.26476v1 Announce Type: new Abstract: Zero-shot image restoration methods with text-to-image latent diffusion models have achieved great success in universal image restoration tasks without

A Constitutive Markov Physics-Informed Neural Operator (MPNO) for Autoregressive Stability in Transient Dynamics

arXiv:2608.25744v1 Announce Type: new Abstract: Neural operators applied to transient-dynamics PDEs with strong discontinuities exhibit autoregressive instability: in concrete-penetration stress-field

A Hierarchical Synergistic Deep Learning Framework Integrating Composition, Structure, and Ionic Transport for Solid-State Electrolyte Discovery

arXiv:2608.25592v1 Announce Type: cross Abstract: Inorganic solid-state electrolytes must combine high room-temperature ionic conductivity, a wide electrochemical window, excellent electronic insulati

A meta-algorithm for ab initio reconstruction of complex mixtures in cryo-EM

arXiv:2608.25388v1 Announce Type: cross Abstract: We describe a systematic approach for spawning and aggregating multi-class cryo-EM reconstruction jobs. This approach formalizes standard ad hoc strat

A Taxonomy of Construction Task Activities for Robot Workers

arXiv:2608.25395v1 Announce Type: new Abstract: Recent vision-language-action models offer a path toward robots with broader repertoires than conventional task-specific systems. Construction deploymen

A Tendon-Driven Five-Fingered Hand with Distributed Tactile Perception for Dexterous Manipulation

arXiv:2608.25547v1 Announce Type: new Abstract: To apply the techniques of embodied artificial intelligence to human-oid robots for complex manipulations, dexterous robotic hands are indispensable, wh

Adaptive Bayes exactly tracks information over intrinsic time

arXiv:2607.08789v2 Announce Type: replace Abstract: Bayesian and multiplicative-weights updates reweight experts, models, or actions from sequential feedback. We show that the regret of any such updat

Advancements in Content-Based Image Retrieval: A Comprehensive Survey of Relevance Feedback Techniques

arXiv:2312.10089v2 Announce Type: replace Abstract: Content-based image retrieval (CBIR) systems have emerged as crucial tools in the field of computer vision, allowing for image search based on visua

Adversarial Training of Linear Models under Stealthy Attacks

arXiv:2608.25681v1 Announce Type: new Abstract: Predictive models are widely used in many fields, but are vulnerable to false data injection attacks. To address this, detection schemes and adversarial

AI/ML Life Cycle Management for Interoperable AI Native RAN

arXiv:2507.18538v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral to the 5G Radio Access Network (RAN), enabling beam manag

Align Then Adapt: Label-Efficient Adapter Learning for Asymmetric Dense Retrieval

arXiv:2604.03403v2 Announce Type: replace-cross Abstract: Dense retrieval systems increasingly face an asymmetry between complex instruction-like queries and relatively simple, static document collect

Anytime Global Tensor Motion Planning

arXiv:2608.25830v1 Announce Type: new Abstract: Global Tensor Motion Planning (GTMP) solves motion planning with batched tensor operations over a layered multipartite graph. We generalize GTMP so that

Apples to Apples? Towards Comparable Crosslingual Language Model Evaluation

arXiv:2608.25089v1 Announce Type: new Abstract: Crosslingual evaluation of language models that enables fair comparisons remains a fundamental challenge in multilingual NLP. Existing studies adopt a v

ARGenSeg: Image Segmentation with Autoregressive Image Generation Model

arXiv:2510.20803v2 Announce Type: replace Abstract: We propose a novel AutoRegressive Generation-based paradigm for image Segmentation (ARGenSeg), achieving multimodal understanding and pixel-level pe

Auditable CT Phenotyping Through Report-derived Radiological Observations

arXiv:2608.25948v1 Announce Type: new Abstract: Medical image foundation models can predict clinical phenotypes from computed tomography (CT), but strong performance leaves open whether they read dise

AutoVerifier: Residual-Guided Non-Parametric Optimization for Reference-Based Answer Verification

arXiv:2608.25637v1 Announce Type: new Abstract: Reference-based verifiers are important for evaluating reasoning models and providing accurate outcome rewards in reinforcement learning with verifiable

BAGEL: Adversarially Constrained Online Convex Optimization under Separation Oracle Access

arXiv:2502.16744v3 Announce Type: replace Abstract: In adversarial Constrained Online Convex Optimization (COCO), a learner selects actions from a fixed convex set while seeking both low regret and lo

Behind the [MASK]: Disentangling Representation and Faithfulness in DAPF-Based Dementia Detection

arXiv:2608.25028v1 Announce Type: new Abstract: Spoken-language analysis via prompt-based domain-adaptive models is a promising direction for low-resource, non-invasive dementia screening, but such mo

Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules

arXiv:2608.25551v1 Announce Type: new Abstract: Stochastic gradient descent (SGD) is typically analyzed at a deterministic horizon chosen before the algorithm is run, even though practical stopping de

Beyond Pairwise Feedback: Listwise Vision-Language Supervision for Preference-Based Reward Learning

arXiv:2608.25350v1 Announce Type: new Abstract: Vision-language models (VLMs) have emerged as a powerful source of supervision for reinforcement learning, enabling agents to leverage rich semantic kno

Beyond Tokens: Probing Higher-Order Epistasis in Learned Protein Representations

arXiv:2608.24953v1 Announce Type: cross Abstract: Protein fitness landscapes contain nonlinear interactions in which mutation effects depend on other residues. We introduce ORBIT, an Order-Resolved Be

Bootstrapping a 4D LiDAR Annotation Tool from Video Foundation Models

arXiv:2608.25418v1 Announce Type: new Abstract: Progress in 4D LiDAR segmentation is bottlenecked by data. Assigning temporally consistent labels across sparse point cloud sequences is costly and hard

BRIDLE: Generalized Self-supervised Learning with Quantization

arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu

Canalization Before Generalization: Grokking as a Dynamical Probe

arXiv:2608.25813v1 Announce Type: new Abstract: For overparameterized neural networks, many solutions can fit the training data equally well while behaving very differently on unseen samples. Grokking

Capacity Overflow: A Blind Spot for Backdoor Attacks in Vision MoE

arXiv:2608.25371v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent paradigm for scaling Vision Transformers efficiently. To ensure computational scalability and prevent ex

CardioFusion-AI: Robust ECG--PPG Fusion for Multimodal Physiological Monitoring Under Signal Degradation

arXiv:2608.26000v1 Announce Type: cross Abstract: Wearable electrocardiogram (ECG) and photoplethysmogram (PPG) sensors are complementary but individually fragile: motion artifact, poor contact, and s

Clearing the Underbrush: AI-Enhanced RF Interference Suppression

arXiv:2608.24974v1 Announce Type: new Abstract: AI-based structured interference rejection has grown more popular because deep learning approaches can outperform traditional methods by jointly conside

Cluster-Dags as Powerful Background Knowledge For Causal Discovery

arXiv:2512.10032v3 Announce Type: replace Abstract: Finding cause-effect relationships is of key importance in science. Causal discovery aims to recover a graph from data that succinctly describes the

Common-Center Geometry and Certified Radial Reconstruction for Energy-Form Full Conformal Regions

arXiv:2608.24964v1 Announce Type: cross Abstract: This note studies the geometry of full conformal prediction (FullCP) regions generated by an empirical energy-form pairwise score. Candidate-score con

ConfAL-WM: Confidence-Guided Active Learning for Action-Conditioned World Models

arXiv:2608.25572v1 Announce Type: new Abstract: Action-conditioned world models have become an important foundation for embodied prediction, planning, and synthetic data generation, but their errors u

Continually learning neural-operator surrogate for three-dimensional airborne electromagnetic Bayesian inversion

arXiv:2608.25932v1 Announce Type: cross Abstract: Three-dimensional probabilistic inversion of time-domain airborne electromagnetic (AEM) data is limited by the cost of the forward solve. Even though

Data-driven Effective Modeling of Stochastic Chemical Reaction Networks

arXiv:2608.25421v1 Announce Type: cross Abstract: The Stochastic Simulation Algorithm (SSA), widely considered an exact algorithm for stochastic chemical reaction networks, suffers from high computati

DCGC: Draft-Conditioned Global Correction for Complex Reasoning with Masked Diffusion Models

arXiv:2608.25428v1 Announce Type: new Abstract: Correcting flawed reasoning traces remains a significant challenge for Large Language Models (LLMs), whose autoregressive generation can propagate early

DeCO: Discriminative Evidence Composition for Fine-Grained Dataset Distillation

arXiv:2608.25480v1 Announce Type: new Abstract: Dataset distillation compresses a large training set into a compact synthetic set while preserving its downstream utility. However, existing methods pri

Deep greedy unfolding: Sorting out argsorting in greedy sparse recovery algorithms

arXiv:2505.15661v2 Announce Type: replace Abstract: Gradient-based learning imposes (deep) neural networks to be differentiable at all steps. This includes model-based architectures constructed by unr

DEFUSE: Generalizable Backdoor Defense for Self-Supervised Encoders with Generative Priors

arXiv:2608.25851v1 Announce Type: new Abstract: Self-supervised learning (SSL) encoders are vulnerable to backdoor attacks, posing threats to both visual SSL encoders and vision-language encoders. Exi

Development of a Voice-Controlled Tendon-Driven Bionic Hand

arXiv:2608.25222v1 Announce Type: new Abstract: The impairment of the hands can seriously affect the abilities of every individual to perform the every-day activity, so the design of stable and contro

Difficulty-Aware Sample Allocation for Adaptive Data Augmentation in Semantic Segmentation

arXiv:2608.25710v1 Announce Type: new Abstract: Data augmentation is a standard component of modern semantic segmentation pipelines, but most augmentation techniques allocate transformations uniformly

Do Vision-Language Models Agree on the Affective Qualities of Shape? A Cross-Model Audit for Generative Design Interfaces

arXiv:2608.25876v1 Announce Type: cross Abstract: Generative design interfaces increasingly expose semantic controls that let users steer output with concepts such as 'more elegant' or 'more minimalis

Dynamically-Consistent Trajectory Optimization for Legged Robots via Contact Point Decomposition

arXiv:2510.24069v2 Announce Type: replace Abstract: To generate reliable motion for legged robots through trajectory optimization, it is crucial to simultaneously compute the robot's path and contact

Efficient Estimation of High Information Projections using Nearest Neighbours

arXiv:2608.25887v1 Announce Type: cross Abstract: An intuitive method for dimensionality reduction is proposed, which is highly effective for finding interesting projections of multivariate data. Foll

Efficient Training with Foresight: Multi-Token Auxiliary Supervision for Autoregressive Image Generation

arXiv:2608.25386v1 Announce Type: new Abstract: Autoregressive (AR) image generation has shown strong potential for scalable high-fidelity synthesis by modeling images as discrete token sequences. How