Search: “framework”

BiasBench: A reproducible benchmark for tuning the biases of event cameras

arXiv:2504.18235v2 Announce Type: replace Abstract: Event-based cameras are bio-inspired sensors that detect light changes asynchronously for each pixel. They are increasingly used in fields like comp

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Applications

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives

DGX agent

arXiv:2509.21256v3 Announce Type: replace Abstract: Non-prehensile manipulation, encompassing ungraspable actions such as pushing, poking, pivoting, and wrapping, remains underexplored due to its cont

applicationsarxiv-cs-ro

10 Jul 2026

BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression

arXiv:2607.08643v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly constrained by memory capacity, weight bandwidth, and checkpoint storage during deployment. Existing low-b

local-aiarxiv-cs-lg

Bridging Modal Isolation in Interleaved Thinking: Supervising Modality Transitions via Stepwise Reinforcement

arXiv:2606.12886v2 Announce Type: replace-cross Abstract: Interleaved thinking, where a unified multimodal model alternates between textual reasoning and visual generation, has shown promise on spatia

researcharxiv-cs-ai

COALA: Robust Contextualized Speech-augmented Language Modeling for ASR via Contrastive Regularizer and Biasing Score Estimation

model-releasesarxiv-cs-cl

arXiv:2607.08117v1 Announce Type: new Abstract: Contextual biasing seeks to integrate external knowledge into automatic speech recognition (ASR) systems to accurately recognize domain-specific entitie

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems

arXiv:2607.08013v1 Announce Type: new Abstract: Federated Learning (FL) empowers multiple clients to collaboratively learn a model, enlarging the training data of each client for high accuracy while p

local-aiarxiv-cs-lg

Communication-Efficient Byzantine-Robust Federated Conformal Prediction via Partial Model Sharing

arXiv:2602.18396v2 Announce Type: replace Abstract: We propose PRISM-FCP (Partial shaRing and robust calIbration with Statistical Margins for Federated Conformal Prediction), a communication-efficient

Concretized Proposition Prompting Resolves Composition-Knowledge Dichotomy in Large Language Models

arXiv:2607.08018v1 Announce Type: new Abstract: LLMs often struggle to balance compositionality with knowledgeability, a challenge we define as Composition-Knowledge Dichotomy. To address this, we pro

ConRad: Efficient Conformal Prediction for Radiomics

arXiv:2607.08084v1 Announce Type: cross Abstract: Radiomic features derived from medical images and segmentation masks are used to support decision making in clinical imaging pipelines. In practice, t

ContactMimic: Humanoid Object Interaction via Contact Control

arXiv:2607.08742v1 Announce Type: new Abstract: Keypoint tracking alone is insufficient for object interaction tasks such as sitting on a chair, wiping a board, or pushing furniture, where the robot c

safetyarxiv-cs-ro

Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future Directions

arXiv:2607.08164v1 Announce Type: new Abstract: Deep neural nets achieve remarkable performance when training and test data share the same distribution, but this assumption frequently breaks in real-w

Curriculum Learning for Efficient Chain-of-Thought Distillation via Structure-Aware Masking and GRPO

arXiv:2602.17686v4 Announce Type: replace-cross Abstract: Distilling Chain-of-Thought (CoT) reasoning from large language models into compact student models presents a fundamental challenge: teacher r

safetyarxiv-cs-ai

Applications

D-CLIPSE: Distributed Consensus-based Localization with Passive Listening on Shared State Exchange

arXiv:2607.07995v1 Announce Type: new Abstract: Multi-robot localization that is accurate and consistent is imperative for downstream tasks such as planning and control. Centralized filtering approach

applicationsarxiv-cs-ro

Deep Learning Method for Stationary Distribution of Reflected Brownian Motion

arXiv:2607.08091v1 Announce Type: cross Abstract: The stationary distribution of reflected Brownian motion (RBM) plays an important role in the analysis of high-dimensional stochastic systems, yet clo

researcharxiv-cs-ai

Agents

DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment

arXiv:2607.07820v1 Announce Type: new Abstract: Training tool-use agents to improve from their own experience remains challenging, as supervised fine-tuning relies on fixed teacher-distilled trajector

agentsarxiv-cs-cl

Tutorials

Deploying quantized models on Amazon SageMaker AI with Unsloth

In this post, you will learn four deployment patterns for taking models that have already been quantized with Unsloth and deploying them on AWS infrastructure. The patterns use Amazon Elastic Compute

tutorialsaws-ml-blog

Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

model-releasesarxiv-cs-cl

arXiv:2607.08208v1 Announce Type: new Abstract: This paper describes our self-designed system for Task 1 of the MLC-SLM 2026 Challenge for multilingual two-speaker conversational speech. The system co

Do Transformations Reveal the Truth? Generative Residual Learning for Generalized AI-Generated Image Detection

arXiv:2607.08674v1 Announce Type: new Abstract: The rapid advancement of generative AI has enabled the creation of highly realistic deepfake media, posing significant threats, including misinformation

Douglas-Rachford Splitting for Group-Sparse Feedback Linear-Quadratic Control

arXiv:2507.19895v4 Announce Type: replace-cross Abstract: In this paper, we study the distributed linear quadratic problem with fixed communication topology (DFT-LQ) and the sparse feedback linear qua

Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text

arXiv:2607.08490v1 Announce Type: new Abstract: Biomedical language evolves rapidly as new discoveries emerge, causing traditional text models to lose semantic fidelity over time. Static embeddings an

researcharxiv-cs-ai

Dynamics of Gradient Descent with Large Step Size Near a Manifold of Flat Minima

arXiv:2607.08380v1 Announce Type: new Abstract: An important quantity in the theory of gradient descent (GD) is the sharpness, defined as the largest eigenvalue of the objective Hessian. Classical ana

EdgeRefine: Privacy-Utility Balance for Graphs via Jaccard Sampling under Edge Differential Privacy

arXiv:2607.08659v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have shown considerable success in learning from graph-structured data, but their use in privacy-sensitive areas remains di

EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data

arXiv:2607.08436v1 Announce Type: cross Abstract: Egocentric human data offers scalable supervision for robot manipulation. However, behavior cloning entangles transferable content like objects, scene

safetyarxiv-cs-ai

Applications

Eigenvalue Calibration for Semantic Embeddings of Large Language Models

arXiv:2607.08377v1 Announce Type: new Abstract: Uncertainty quantification is central to the reliable deployment of large language models (LLMs), and eigenvalues of semantic embeddings have recently e

applicationsarxiv-cs-lg

Enhancing the KidSat Model: Integrating Geographical Encoding and Data Quality Assessment for Childhood Poverty Prediction

arXiv:2607.08281v1 Announce Type: new Abstract: Accurate poverty mapping using satellite imagery is often hindered by (i) noisy and sparse survey-derived supervision, (ii) image quality issues such as

Expressivity and Statistical Trade-offs in Diffusion Policy Learning

arXiv:2607.07967v1 Announce Type: cross Abstract: Diffusion-based policies have recently emerged as powerful policy parameterizations for reinforcement learning, representing state-conditioned action

safetyarxiv-cs-lg

Fair Document Valuation in LLM Summaries via Shapley Values

arXiv:2505.23842v5 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly power search engines and AI assistants that retrieve and summarize content from many sources. By serving a

researcharxiv-cs-cl

FPGN: Redefining Ultra-Fast Programmable Gate-based Neural Acceleration with Differentiable LUTs

arXiv:2607.08427v1 Announce Type: cross Abstract: Achieving nanosecond-scale inference latency for deep neural networks (DNNs) has become a primary architectural concern for latency-critical applicati

local-aiarxiv-cs-lg

From Theory to Application: A Practical Introduction to Neural Operators in Scientific Computing

arXiv:2503.05598v3 Announce Type: replace-cross Abstract: This review examines neural operator architectures for learning solution operators of parametric partial differential equations (PDEs), with a

Frontier and Center: Who evaluates the evaluations?

model-releasesgoogle-cloud-ai

Editor’s note: Some of the most interesting questions in AI are being asked by information theoreticians, around how to provide context to an emerging class of AI agents. A few weeks ago, we waded int

Agents

FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation

arXiv:2607.08359v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs

agentsarxiv-cs-ai

Generalization Theory for Through-the-Wall Radar Human Activity Recognition

model-releasesarxiv-cs-lg

arXiv:2607.08144v1 Announce Type: cross Abstract: Through-the-wall radar (TWR) human activity recognition (HAR) is important for non-line-of-sight indoor sensing, security monitoring, and emergency re

Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction

arXiv:2607.08769v1 Announce Type: new Abstract: Scaling 3D Gaussian Splatting (3DGS) to large outdoor scenes is costly in both data acquisition and computation. Adopting panoramic images with equirect

Applications

GradInf: Gradient Estimation as Probabilistic Inference

arXiv:2607.07840v1 Announce Type: cross Abstract: Gradient estimation -- the task of computing the gradient of the expected value of a probabilistic program -- has diverse applications in scientific c

applicationsarxiv-cs-lg

Graph-Loc: Robust Graph-Based LiDAR Pose Tracking with Compact Structural Map Priors under Low Observability and Occlusion

arXiv:2602.08417v2 Announce Type: replace Abstract: Map-based LiDAR pose tracking is essential for long-term autonomous operation, where onboard map priors need be compact for scalable storage and fas

local-aiarxiv-cs-ro

GRE-Diff: Gaussian Room Embeddings for Structured Layout Diffusion

arXiv:2607.08086v1 Announce Type: new Abstract: Designing functional and aesthetically coherent floor plans requires exploring a vast space of possible room arrangements, a task that quickly becomes o

GSurf: Learning Signed Distance Fields from Splatting Opaque Gaussians for High-quality 3D Reconstruction

arXiv:2411.15723v4 Announce Type: replace Abstract: High-fidelity surface reconstruction from multi-view images is a core problem in 3D computer vision. While neural implicit surfaces like SDFs offer

Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents

arXiv:2607.08448v1 Announce Type: new Abstract: Language-conditioned manipulation requires both precise contact-rich control and robust reasoning over language, scenes, and long horizons. End-to-end V

local-aiarxiv-cs-ro

HoloTetSphere: Unified TetSphere Mesh Reconstruction for Physical Simulations

arXiv:2607.08398v1 Announce Type: cross Abstract: Standard pipelines for physics-ready 3D reconstruction rely on a decoupled two-stage paradigm: extracting surface geometry followed by an error-prone

ICDAR 2026 HIPE-OCRepair Competition on LLM-Assisted OCR Post-Correction for Historical Documents

arXiv:2607.08143v1 Announce Type: cross Abstract: We present the results of HIPE-OCRepair-2026, an ICDAR competition on LLM-assisted OCR post-correction of historical documents. OCR post-correction re

Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation

arXiv:2607.08758v1 Announce Type: new Abstract: Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biol

IFAR: Multi-Perspective and Multi-Level Causal Discovery with LLMs

arXiv:2409.05559v2 Announce Type: replace Abstract: Large language models (LLMs) have developed rapidly, and their reasoning capabilities have become a hot research topic. However, there is still limi

IMProofBench: Benchmarking AI on Research-Level Mathematical Proof Generation

model-releasesarxiv-cs-cl

arXiv:2509.26076v2 Announce Type: replace Abstract: As the mathematical capabilities of large language models (LLMs) improve, it becomes increasingly important to evaluate their performance on researc

In vivo feasibility study of humanoid robots in surgery

arXiv:2607.07972v1 Announce Type: new Abstract: Recent advances in actuation, control and learning have rapidly pushed humanoid robots from a distant vision towards near-term real-world deployment. He

safetyarxiv-cs-ro

Infinity-Parser2 Technical Report

arXiv:2607.07836v1 Announce Type: new Abstract: We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end

It Takes a MAESTRO To Prune Bad Experts

arXiv:2607.08601v1 Announce Type: new Abstract: Sparsely-activated Mixture-of-Experts (MoE) language models achieve remarkable inference efficiency by activating only a small fraction of parameters pe

safetyarxiv-cs-cl

Joint Bayesian Parameter and Model Order Estimation for Low-Rank Probability Mass Tensors

model-releasesarxiv-cs-lg

arXiv:2410.06329v4 Announce Type: replace-cross Abstract: Obtaining a reliable estimate of the joint probability mass function (PMF) of a set of random variables from observed data is a significant ob

Joint Discrete-Continuous Flow Matching for Open-Vocabulary Inverse Design of Multilayer Optical Coatings

model-releasesarxiv-cs-lg

arXiv:2607.08392v1 Announce Type: cross Abstract: Amortized neural inverse design typically remains closed-world: component choices are fixed vocabulary tokens, coordinate grids are frozen at training