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On the Effect of Sampling Diversity in Scaling LLM Inference

arXiv:2502.11027v5 Announce Type: replace Abstract: Large language model (LLM) scaling inference is key to unlocking greater performance, and leveraging diversity has proven an effective way to enhanc

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On the expressivity of deep Heaviside networks

DGX agent

arXiv:2505.00110v2 Announce Type: replace-cross Abstract: We show that deep Heaviside networks (DHNs) have limited expressiveness but that this can be overcome by including either skip connections or

researcharxiv-cs-lg

11 Aug 2026

On the Robustness of LLMs' Internal Representation of Code Correctness

arXiv:2608.08266v1 Announce Type: cross Abstract: Code generated by modern language models often reads naturally. Yet, it also often fails to implement what was asked. This should be no surprise, as r

One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training

arXiv:2608.09403v1 Announce Type: new Abstract: Whole slide images (WSIs) in digital histopathology are acquired at discrete magnification levels encoding complementary diagnostic information from glo

Online Learning of Scale Parameters in Score-Driven Filters

arXiv:2608.09218v1 Announce Type: new Abstract: Score-driven filters multiply a scaled log-likelihood score by a gain that controls the update magnitude. We treat this gain as a decision variable and

Open-World Semantic Segmentation with Sensitivity Modeling

arXiv:2608.08308v1 Announce Type: cross Abstract: Modern vision systems must operate in 'open-world' settings, where models must recognize known categories and detect unseen or anomalous content. Conv

Opportunity Is Not Realizability: Selection-Valid Diagnostics for Multi-LLM Routing

arXiv:2608.08265v1 Announce Type: new Abstract: Oracle routing measures how much a pool of language models could gain from per-query selection, but the diagnostic has two flaws: testing against a best

Optimal Learning Under Tsybakov Noise

arXiv:2608.08416v1 Announce Type: new Abstract: Probably Approximately Correct (PAC) learning [Val84] is a fundamental learning model that has been extensively investigated. In this model, H subseteq

Optimal Transport for Machine Learners

arXiv:2505.06589v3 Announce Type: replace-cross Abstract: Modern machine learning repeatedly manipulates probability measures: empirical datasets, generated samples, latent distributions, class-condit

Overcoming Data Scarcity and Confidentiality in Hardware Assurance via Synthetic Generation

arXiv:2608.09914v1 Announce Type: cross Abstract: Hardware assurance relies on scanning electron microscopy (SEM) to verify nanoscale structures, but assembling the large, high-quality datasets requir

PARAGraph: Pathology-Anatomy-Aware Hierarchical Graph for Diabetic Retinopathy Grading

arXiv:2608.08368v1 Announce Type: new Abstract: Diabetic retinopathy (DR) remains a leading cause of vision loss among working-age adults worldwide, making reliable severity grading clinically importa

Parcel2Progression: An Anatomy-aware Longitudinal Framework for Alzheimer's Disease Diagnosis

arXiv:2608.08753v1 Announce Type: new Abstract: Alzheimer's disease (AD) progression is a longitudinal process with subtle pathological cues in the early stages. Yet, computational constraints have li

PatchHead: Learning Spatial Patch Evidence for Generalizable AI-Generated Image Detection

arXiv:2608.09223v1 Announce Type: new Abstract: AI-generated image detectors generalize poorly when their training and test images originate from different generators or datasets. Despite the rich spa

PATH: Next-Interval Prediction via Autoregressive Tree Hierarchy on Tabular Data

arXiv:2608.08078v1 Announce Type: new Abstract: Interval prediction aims to achieve a target coverage level while producing intervals that are as short as possible. Many conformal regression pipelines

PE-Mamba: Bidirectional Selective Layer Aggregation for AI-Generated Image Detection

arXiv:2608.07999v1 Announce Type: new Abstract: AI-generated image (AIGI) detection has become increasingly challenging due to the rapid advancement of generative models and the diminishing gap betwee

PEEL: Parallel Extraction for Long-Horizon Disassembly Planning via Scale-Invariant Sampling

arXiv:2608.08773v1 Announce Type: new Abstract: Long-horizon multi-part object disassembly requires robots to compute feasible sequences of collision-free removal motions, even in the presence of tigh

researcharxiv-cs-ro

PET/CT Radiogenomic Mutation Prediction in Non-Small Cell Lung Cancer Using Multi-Label Learning

arXiv:2608.09721v1 Announce Type: new Abstract: Lung cancer remains one of the leading causes of cancer- related mortality worldwide. Although targeted therapies have improved outcomes for patients wi

PhysX-CoT: Structured Physical Reasoning from a Single Image to Simulation-Ready 3D Assets

arXiv:2608.08053v1 Announce Type: cross Abstract: Simulation-ready 3D assets are central to robotics and embodied AI. Generating them from a single image is usually framed as a vision-language model t

PolypSteer: Counterfactual Endoscopic Synthesis via Training-Free Activation Steering

arXiv:2603.07066v2 Announce Type: replace-cross Abstract: Generative diffusion models are increasingly used for medical imaging data augmentation, but text prompting cannot produce causal training dat

Positioning Generative Artificial Intelligence in STEM Assessment: When to Require, Scaffold, or Restrict Its Use

arXiv:2608.07475v1 Announce Type: cross Abstract: Generative Artificial Intelligence (GenAI) presents a governance challenge for STEM assessment. Unrestricted access can enable task outsourcing that u

PragyaDoc: A Universal Document Intelligence Framework for Multilingual Medical Document Understanding in Low-Resource Settings

arXiv:2608.07478v1 Announce Type: cross Abstract: India's 22 official languages create a critical accessibility barrier: the majority of medical documentation exists exclusively in English, yet the pa

researcharxiv-cs-cl

Predict to Skip: Linear Multistep Feature Forecasting for Efficient Diffusion Transformers

arXiv:2602.18093v2 Announce Type: replace Abstract: Diffusion Transformers (DiT) have emerged as a widely adopted backbone for high-fidelity image and video generation, yet their iterative denoising p

Predictive Failure Detection in Network Hardware Using Thermal Imaging and Deep Learning with Sensor Fusion

arXiv:2608.07582v1 Announce Type: new Abstract: Unplanned network hardware malfunctions can interrupt services and result in expensive downtime in data centers. A deep learning-based predictive mainte

PressureMesh: 3D Human Mesh Estimation from Multi-Device Pressure Images

arXiv:2608.09550v1 Announce Type: new Abstract: Human pose monitoring is crucial in fields such as rehabilitation assessment and human-computer interaction. Due to its privacy-preserving nature, press

Preview-Based Relative-Motion Control of an Insertion Tool for Neural-Thread Placement in Pulsating Tissue

arXiv:2608.08860v1 Announce Type: cross Abstract: Robotic neural-thread placement requires regulating the insertion-tool tip relative to tissue that moves with cardiac and respiratory pulsation. This

researcharxiv-cs-ro

PRISM: A Predictive Protocol for Permutation Optimization via Landscape Diagnostics

arXiv:2608.08344v1 Announce Type: cross Abstract: Permutation optimization arises whenever the components of a system are fixed but their ordering affects performance. We introduce PRISM, a predictive

PRISM-Delta: Differential Subspace Steering for Prompt Highlighting in Large Language Models

arXiv:2603.10705v2 Announce Type: replace Abstract: Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing

researcharxiv-cs-cl

ProbSPARQL: Querying Knowledge Graphs with Multi-dimensional, Uncertain Numeric Data

arXiv:2607.18262v2 Announce Type: replace Abstract: The SFB 1574 Circular Factory is building a shared knowledge graph infrastructure for integrating data about returned products. A central challenge

Projection-Retraction MPPI: Exact Constraint-Manifold Control for Manipulators

arXiv:2608.07573v1 Announce Type: new Abstract: Model Predictive Path Integral (MPPI) control is widely used in manipulation for its gradient-free, parallel handling of non-convex costs. Manipulation

researcharxiv-cs-ro

Prompt Embedding Probes (PEP): Hallucination Detection in LLMs from Hidden States

arXiv:2608.08024v1 Announce Type: cross Abstract: Large language models (LLMs) can generate fluent and useful responses but remain prone to hallucinations. We introduce Prompt Embedding Probes (PEP),

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks

arXiv:2502.00803v3 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have earned high expectations in solving partial differential equations (PDEs), but their optimization usua

Prospects of Finding a ML Engineering Job [D]

researchr-machinelearning

Hello all, I am wondering if a transition from a Ph.D. in electrical engineering (Quantum optics/photonics) to a job in ML is a reasonable aspiration. Personally, I have extensive software development

Quality-Diversity Stress Tests for Process Reward Models:What Archive Coverage Can and Cannot Certify

arXiv:2608.08008v1 Announce Type: new Abstract: Process reward models (PRMs) score intermediate reasoning steps and are widely used for search, ranking, and training, but optimization can exploit thes

Quantization Degradation in Large Language Models: A Signal-Noise Perspective

arXiv:2608.08188v1 Announce Type: new Abstract: Post-training quantization reduces the deployment cost of large language models, yet how severely a quantized model degrades is not determined by bit-wi

R3S: Refining and Recovering Reinforcement Signals for Multilingual Understanding and Reasoning

arXiv:2602.05940v2 Announce Type: replace Abstract: Large reasoning models often default to English reasoning when processing non-English questions, yet their performance drops substantially when reas

researcharxiv-cs-cl

RAG-Audio: Retrieval-Augmented Generation for Faithful Brain-to-Audio Reconstruction

arXiv:2608.09331v1 Announce Type: cross Abstract: Brain-to-audio reconstruction is limited by prior domination: when a pretrained generator is conditioned on a weak neural signal, it produces realisti

RankGuide: Tensor-Rank-Guided Routing and Steering for Efficient Reasoning

arXiv:2604.16694v2 Announce Type: replace Abstract: Large reasoning models (LRMs) enhance problem-solving capabilities by generating explicit multi-step chains of thought (CoT) reasoning; however, the

RAVEN-Eval: Rubric-Guided Automatic Evaluation for AI Video Generation Models Based on LMM Preference Judgement

arXiv:2608.09111v1 Announce Type: new Abstract: AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-a

RAVEN: Frozen Random Graph Reservoirs with Physics-Informed Interaction Fingerprints for Protein-Ligand Binding Affinity Prediction

arXiv:2608.09099v1 Announce Type: new Abstract: Quantitative estimation of protein-ligand binding affinity from three-dimensional complex structures is a fundamental task in structure-based computatio

Recurrent Neural Networks Beyond Time: Learning from Multiple Ordered Projections

arXiv:2608.09690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) are widely used for sequence learning, yet their application is commonly associated with temporal data, although recurr

ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation

arXiv:2601.07121v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used not only for problem solving but also for creative ideation; however, generating ideas that

Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification

arXiv:2608.09512v1 Announce Type: new Abstract: Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and tempo

ResemBrick: Brick Reconstruction from Photographs with Perceptual Fidelity and Buildability

arXiv:2608.09597v1 Announce Type: new Abstract: Producing a hand-buildable, colored brick model of a 3D object from a few casual photographs is a clean testbed for a broader challenge: generating 3D c

Resolution Meets Reduction: Efficient Visual Context for 3D Radiology Report Generation

arXiv:2608.08713v1 Announce Type: cross Abstract: Vision-language models offer a promising path toward automating radiology report generation, but applying them to full 3D CT volumes poses substantial

Rethinking Learning-Based Influence Maximization: Simple Neural Surrogates and Native Discrete Search

arXiv:2608.08406v1 Announce Type: new Abstract: Existing learning-based influence maximization frameworks rely heavily on complex neural architectures and continuous optimization over seed representat

Rethinking Reasoning with MDLMs: Early Exits, Post-hoc Reasoning, and Beyond

arXiv:2510.19990v2 Announce Type: replace Abstract: The reasoning paradigm, where language models reason before answering, has enabled breakthroughs on tasks such as mathematical problem-solving. Whil

Revision or Re-Solving? Decomposing Second-Pass Gains in Multi-LLM Pipelines

arXiv:2604.01029v2 Announce Type: replace-cross Abstract: Multi-LLM revision pipelines, in which a second model reviews and improves a draft produced by a first, are widely assumed to derive their gai

Revisiting the Current Frame: Physical-Trace-Guided Network Output Correction for Video Restoration

arXiv:2608.09342v1 Announce Type: new Abstract: Video restoration methods exploit temporal information to recover information missing from degraded observations. However, reference frames within the s