Search: “inference”

BatteryPass-12K: The First Dataset for the Novel Digital Battery Passport Conformance Task

model-releasesarxiv-cs-cl

arXiv:2604.26986v1 Announce Type: new Abstract: We introduce a novel task of digital battery passport (DBP) conformance classification and introduce the first public benchmark for the task: BatteryPas

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EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures

DGX agent

arXiv:2604.27004v1 Announce Type: cross Abstract: We propose EdgeSpike, a co-designed spiking neural network (SNN) framework for autonomous low-power sensing in edge Internet of Things (IoT) architect

model-releasesarxiv-cs-lg

1 May 2026

From Unstructured Recall to Schema-Grounded Memory: Reliable AI Memory via Iterative, Schema-Aware Extraction

model-releasesarxiv-cs-ai

arXiv:2604.27906v1 Announce Type: new Abstract: Persistent AI memory is often reduced to a retrieval problem: store prior interactions as text, embed them, and ask the model to recover relevant contex

Hypnopaedia-Aware Machine Unlearning via Psychometrics of Artificial Mental Imagery

arXiv:2410.05284v2 Announce Type: replace-cross Abstract: Neural backdoors represent insidious cybersecurity loopholes that render learning machinery vulnerable to unauthorised manipulations, potentia

researcharxiv-cs-ai

LUNA: LUT-Based Neural Architecture for Fast and Low-Cost Qubit Readout

arXiv:2512.07808v2 Announce Type: replace-cross Abstract: Qubit readout is a critical operation in quantum computing systems, which maps the analog response of qubits into discrete classical states. D

Hardware

MARS: Efficient, Adaptive Co-Scheduling for Heterogeneous Agentic Systems

arXiv:2604.26963v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as the execution core of autonomous agents rather than as standalone text generators. Agentic w

hardwarearxiv-cs-lg

MotuBrain: An Advanced World Action Model for Robot Control

arXiv:2604.27792v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models achieve strong semantic generalization but often lack fine-grained modeling of world dynamics. Recent work explores

safetyarxiv-cs-ro

Physical Foundation Models: Fixed hardware implementations of large-scale neural networks

model-releasesarxiv-cs-lg

arXiv:2604.27911v1 Announce Type: new Abstract: Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks --

YOSE: You Only Select Essential Tokens for Efficient DiT-based Video Object Removal

arXiv:2604.27322v1 Announce Type: new Abstract: Recent advances in Diffusion Transformer (DiT)-based video generation technologies have shown impressive results for video object removal. However, thes

A Dual-Task Paradigm to Investigate Sentence Comprehension Strategies in Language Models

arXiv:2604.26351v1 Announce Type: new Abstract: Language models (LMs) behave more like humans when their cognitive resources are restricted, particularly in predicting sentence processing costs such a

A Priori Sampling of Transition States with Guided Diffusion

arXiv:2603.25980v2 Announce Type: replace-cross Abstract: Transition states, the first-order saddle points on the potential energy surfaces, govern the kinetics and mechanisms of chemical reactions an

Adaptive Transform Coding for Semantic Compression

arXiv:2604.26492v1 Announce Type: cross Abstract: Visual data compression is shifting from human-centered reconstruction to machine-oriented representation coding. In this setting, an image is often m

Beyond Shortcuts: Mitigating Visual Illusions in Frozen VLMs via Qualitative Reasoning

arXiv:2604.26250v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) have achieved state-of-the-art performance in general visual tasks, their perceptual robustness remains remarkably b

safetyarxiv-cs-cv

Breaking the Autoregressive Chain: Hyper-Parallel Decoding for Efficient LLM-Based Attribute Value Extraction

arXiv:2604.26209v1 Announce Type: cross Abstract: Some text generation tasks, such as Attribute Value Extraction (AVE), require decoding multiple independent sequences from the same document context.

researcharxiv-cs-ai

DiffAnon: Diffusion-based Prosody Control for Voice Anonymization

arXiv:2604.26281v1 Announce Type: cross Abstract: To preserve or not to preserve prosody is a central question in voice anonymization. Prosody conveys meaning and affect, yet is tightly coupled with s

Entropy Centroids as Intrinsic Rewards for Test-Time Scaling

model-releasesarxiv-cs-ai

arXiv:2604.26173v1 Announce Type: cross Abstract: An effective way to scale up test-time compute of large language models is to sample multiple responses and then select the best one, as in Grok Heavy

Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs

arXiv:2510.06735v2 Announce Type: replace Abstract: Bayesian causal discovery benefits from prior information elicited from domain experts, and in heterogeneous domains any prior knowledge would be ba

Laplace Approximation for Bayesian Tensor Network Kernel Machines

arXiv:2604.26673v1 Announce Type: cross Abstract: Uncertainty estimation is essential for robust decision-making in the presence of ambiguous or out-of-distribution inputs. Gaussian Processes (GPs) ar

Learning Vision-Based Omnidirectional Navigation: A Teacher-Student Approach Using Monocular Depth Estimation

arXiv:2603.01999v2 Announce Type: replace-cross Abstract: Reliable obstacle avoidance in industrial settings demands 3D scene understanding, but widely used 2D LiDAR sensors perceive only a single hor

safetyarxiv-cs-cv

LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation

arXiv:2507.01449v3 Announce Type: replace Abstract: Speculative decoding (SD), where a small draft model is employed to propose draft tokens in advance and then the target model validates them in para

Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2604.26508v1 Announce Type: cross Abstract: Deploying Vision-Language Models (VLMs) on edge devices remains challenging due to their substantial computational and memory demands, which exceed th

Seeking Consensus: Geometric-Semantic On-the-Fly Recalibration for Open-Vocabulary Remote Sensing Semantic Segmentation

arXiv:2604.26221v1 Announce Type: cross Abstract: Open-vocabulary semantic segmentation (OVSS) in remote sensing images is a promising task that employs textual descriptions for identifying undefined

safetyarxiv-cs-ai

Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

arXiv:2604.26694v1 Announce Type: cross Abstract: We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruc

researcharxiv-cs-ai

Applications

Bayesian Inverse Transition Learning: Learning Dynamics From Near-Optimal Trajectories

arXiv:2411.05174v2 Announce Type: replace Abstract: We consider the problem of estimating the transition dynamics T^* from near-optimal expert trajectories in the context of offline model-based reinfo

applicationsarxiv-cs-lg

Can We Change the Stroke Size for Easier Diffusion?

arXiv:2603.26783v2 Announce Type: replace Abstract: Diffusion models can be challenged in the low signal-to-noise regime, where they have to make pixel-level predictions despite the presence of high n

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding

arXiv:2602.01785v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable success in source code understanding, yet as software systems grow in scale, computational eff

Tutorials

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity

arXiv:2603.20645v2 Announce Type: replace Abstract: Diffusion models have become a leading framework in generative modeling, yet their theoretical understanding -- especially for high-dimensional data

tutorialsarxiv-cs-lg

DouC: Dual-Branch CLIP for Training-Free Open-Vocabulary Segmentation

arXiv:2604.24997v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation requires assigning pixel-level semantic labels while supporting an open and unrestricted set of categories. Traini

local-aiarxiv-cs-cv

From Cursed to Competitive: Closing the ZO-FO Gap via Input-to-State Stability

arXiv:2604.25372v1 Announce Type: cross Abstract: While it is generally understood that zeroth-order (ZO) algorithms have an extra dependency on their number of iterations for any choice of parameters

How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning

arXiv:2603.01070v2 Announce Type: replace Abstract: Solving complex geometric problems inherently requires interleaved reasoning: a tight alternation between constructing diagrams and performing logic

safetyarxiv-cs-cl

Investigation into In-Context Learning Capabilities of Transformers

model-releasesarxiv-cs-lg

arXiv:2604.25858v1 Announce Type: new Abstract: Transformers have demonstrated a strong ability for in-context learning (ICL), enabling models to solve previously unseen tasks using only example input

Learning biophysical models of gene regulation with probability flow matching

arXiv:2604.25062v1 Announce Type: cross Abstract: Cellular differentiation is governed by gene regulatory networks, the high-dimensional stochastic biochemical systems that determine the transcription

Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Tracking

arXiv:2604.25405v1 Announce Type: new Abstract: Camera-based 3D object detection and tracking are central to autonomous driving, yet precise 3D object localization remains fundamentally constrained by

local-aiarxiv-cs-cv

Lightweight Real-Time Rendering Parameter Optimization via XGBoost-Driven Lookup Tables

model-releasesarxiv-cs-cv

arXiv:2604.25178v1 Announce Type: new Abstract: Achieving a desirable balance between rendering quality and real-time performance is a long-standing challenge in modern game and rendering engines, par

Making AI-Assisted Grant Evaluation Auditable without Exposing the Model

arXiv:2604.25200v1 Announce Type: cross Abstract: Public agencies are beginning to consider large language models (LLMs) as decision-support tools for grant evaluation. This creates a practical govern

Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling

arXiv:2604.25578v1 Announce Type: new Abstract: We present Marco-MoE, a suite of fully open multilingual sparse Mixture-of-Experts (MoE) models. Marco-MoE features a highly sparse design in which only

MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment

arXiv:2603.15954v2 Announce Type: replace Abstract: Real-time AI experiences call for on-device large language models (OD-LLMs) optimized for efficient deployment on resource-constrained hardware. The

local-aiarxiv-cs-lg

Multimodal Contextualized Support for Enhancing Video Retrieval System

arXiv:2412.07584v2 Announce Type: replace Abstract: Current video retrieval systems, especially those used in competitions, primarily focus on querying individual keyframes or images rather than encod

Mutual Forcing: Dual-Mode Self-Evolution for Fast Autoregressive Audio-Video Character Generation

arXiv:2604.25819v1 Announce Type: new Abstract: In this work, we propose Mutual Forcing, a framework for fast autoregressive audio-video generation with long-horizon audio-video synchronization. Our a

Null Measurability at the Symmetrization Interface in VC Learning

arXiv:2604.25028v1 Announce Type: new Abstract: Recent work revisiting measurability in the fundamental theorem of statistical learning imposes Borel measurability of ghost-gap suprema. We show that,

QFlash: Bridging Quantization and Memory Efficiency in Vision Transformer Attention

arXiv:2604.25306v1 Announce Type: new Abstract: FlashAttention improves efficiency through tiling, but its online softmax still relies on floating-point arithmetic for numerical stability, making full

RABC-Net: Reliability-Aware Annotation-Free Skin Lesion Segmentation for Low-Resource Dermoscopy

arXiv:2604.05594v2 Announce Type: replace Abstract: Pixel-level annotation is costly in low-resource dermoscopy. We present RABC-Net, a reliability-aware annotation-free segmentation system that combi

local-aiarxiv-cs-cv

Applications

Robust Deepfake Detection: Mitigating Spatial Attention Drift via Calibrated Complementary Ensembles

arXiv:2604.25889v1 Announce Type: new Abstract: Current deepfake detection models achieve state-of-the-art performance on pristine academic datasets but suffer severe spatial attention drift under rea

applicationsarxiv-cs-cv

SARE: Sample-wise Adaptive Reasoning for Training-free Fine-grained Visual Recognition

model-releasesarxiv-cs-cv

arXiv:2603.17729v3 Announce Type: replace Abstract: Recent advances in Large Vision-Language Models (LVLMs) have enabled training-free Fine-Grained Visual Recognition (FGVR). However, effectively expl

Self-DACE++: Robust Low-Light Enhancement via Efficient Adaptive Curve Estimation

model-releasesarxiv-cs-cv

arXiv:2604.25367v1 Announce Type: new Abstract: In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our prev

The Role of Symmetry in Optimizing Overparameterized Networks

arXiv:2604.25150v1 Announce Type: new Abstract: Overparameterization is central to the success of deep learning, yet the mechanisms by which it improves optimization remain incompletely understood. We

Towards Robust Deep Learning-based Rumex Obtusifolius Detection from Drone Images

arXiv:2604.25316v1 Announce Type: new Abstract: Domain adaptation (DA) addresses the challenge of transferring a machine learning model trained on a source domain to a target domain with a different d

A Divergence-Based Method for Weighting and Averaging Model Predictions

arXiv:2604.24172v1 Announce Type: cross Abstract: This paper uses a minimum divergence framework to introduce a new way of calculating model weights that can be used to average probabilistic predictio