Search: “framework”

MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models

model-releasesarxiv-cs-lg

arXiv:2610.09092v1 Announce Type: new Abstract: State Space Models (SSMs) offer an efficient alternative to Transformers for sequence modeling, yet conditioning pre-trained SSMs for iterative generati

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Marrying Pricing and Advertising with LLMs

DGX agent

arXiv:2610.09985v1 Announce Type: cross Abstract: We study a sequential pricing problem in which a seller jointly posts a price and an advertisement generated by a large language model (LLM). The sell

safetyarxiv-cs-lg

8 Oct 2026

Masked Feature Encoding for Large-Scale Whole Slide Image Representation

arXiv:2610.10225v1 Announce Type: new Abstract: Whole slide image (WSI) analysis in computational pathology follows a multiple instance learning (MIL) pipeline where patch embeddings are extracted ind

local-aiarxiv-cs-cv

MimicX: Policy-in-the-Loop Supervision Refinement for Video-Driven Humanoid Motion Tracking

arXiv:2610.09055v1 Announce Type: new Abstract: Human videos provide rich motion targets for humanoid learning, yet visually plausible references can still produce persistent failures under physics-ba

safetyarxiv-cs-ro

MIRROR: From Imitation to Internalization in LLM Personalization

arXiv:2610.09795v1 Announce Type: new Abstract: The demand for personalized LLMs is shifting from style imitation toward content quality. We investigate whether self-distillation can bridge this gap i

Applications

MoR-MLLM: Mixture of Recursions for Efficient Multimodal Large Language Models

arXiv:2610.08830v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across vision and language tasks. However, their massive co

applicationsarxiv-cs-cv

MORA: Modeling Observed Changes for Drift-Robust Time-Series Anomaly Detection

arXiv:2610.09473v1 Announce Type: new Abstract: Time-series anomaly detection (TSAD) identifies deviations from patterns learned from historical data. In non-stationary settings, distribution drift an

tutorialsarxiv-cs-lg

MORCA: Offline-to-Online Reinforcement Learning for Adaptive Cache Reuse in Video Diffusion Acceleration

arXiv:2610.10457v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve remarkable performance in video synthesis, but their iterative denoising process suffers from high inference laten

tutorialsarxiv-cs-cv

MorphCL: Morphological Contrastive Learning for Inertial-based Human Activity Recognition

arXiv:2610.10245v1 Announce Type: new Abstract: Despite the ubiquity of sensors in wearable and mobile devices and the abundance of human movement data they generate, translating unlabeled recordings

researcharxiv-cs-lg

MovieSTAGE: Scene, Transition, and Global Encoding for Movie-fMRI ADHD Classification

arXiv:2610.09306v1 Announce Type: new Abstract: Naturalistic movie-fMRI provides a shared, temporally structured probe of brain dynamics, yet predictive models commonly rely on whole-run functional co

researcharxiv-cs-lg

Multimodal LLMs Can Learn to Read Brain Signals: A Vision--Language Model for Unified Multi-Task EEG Decoding

arXiv:2610.09355v1 Announce Type: cross Abstract: Learning EEG representations that generalize across cognitive tasks, subjects, and recording conditions remains a key challenge in electroencephalogra

tutorialsarxiv-cs-cv

Agents

Not All Uncertainty Matters: Simulation-in-the-Loop Fast-Slow Reasoning for Decision-Critical Autonomous Driving System

arXiv:2610.09520v1 Announce Type: new Abstract: Large vision-language models (VLMs) provide powerful open-world perception and reasoning for autonomous driving, but their high computational cost and i

agentsarxiv-cs-ro

Applications

NovaPlan: Zero-Shot Long-Horizon Manipulation via Closed-Loop Video Language Planning

arXiv:2602.20119v2 Announce Type: replace-cross Abstract: Solving complex long-horizon robotic tasks requires joint reasoning over abstract task structure and low-level physical interaction. While com

applicationsarxiv-cs-cv

On KL-Regularized Policy Optimization

arXiv:2610.08963v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) for large language model (LLM) agents trains one policy on trajectories generated by another: rollouts come f

On-Policy Distillation Teaches New Skills but Not New Knowledge

arXiv:2610.09639v1 Announce Type: new Abstract: On-policy distillation (OPD) strengthens language-model reasoning, yet whether students acquire new factual knowledge or compositional skill for multi-s

One Frame, Full Heartbeat: ECG-Free 4D Cardiac Cine MRI Synthesis via Radial-Decomposed Flow Matching

arXiv:2610.09185v1 Announce Type: new Abstract: Cine cardiovascular magnetic resonance (CMR) captures the cardiac cycle as a four-dimensional (4D) sequence, but standard acquisition requires electroca

One Frame, Full Heartbeat: ECG-Free Cardiac Cine MRI Synthesis via Phase-Conditioned Flow Matching

arXiv:2610.09397v1 Announce Type: new Abstract: Cine cardiovascular magnetic resonance (CMR) analysis relies on multi-frame sequences capturing the full cardiac cycle. However, standard multi-frame ac

Online Resource Allocation with an Endogenous Markov State: Fewer LP Solves Earn More

model-releasesarxiv-cs-lg

arXiv:2610.09577v1 Announce Type: new Abstract: We study finite-horizon online resource allocation with i.i.d. requests and an endogenous Markov state on a finite state space: each action affects the

OnlineQAT: On-Policy Distillation for Ultra-Low-Bit Large Language Models

arXiv:2610.09346v1 Announce Type: new Abstract: Quantization-aware training (QAT) can recover much of the accuracy lost when large language models are compressed below four bits. Existing re- covery s

OrBIT: Structure-Guided Embedding Compression

arXiv:2610.10385v1 Announce Type: new Abstract: Embedding tables are among the largest components of modern language models. Most compression methods fix a coding geometry such as coordinate blocks, l

local-aiarxiv-cs-lg

Oscillatory Neural Dynamics over Sheaves

arXiv:2610.10018v1 Announce Type: new Abstract: Effective long-range propagation remains a central challenge in graph neural networks, as increasing a model's propagation depth does not guarantee that

researcharxiv-cs-lg

PARC-Loc: Text-to-Point-Cloud Localization with Partial Assignment and Relational Consistency

arXiv:2610.09761v1 Announce Type: cross Abstract: Text-to-point-cloud localization estimates a position in a city-scale 3D map from descriptions of surrounding objects. Existing coarse-to-fine methods

tutorialsarxiv-cs-cl

Performance at What Cost? A Sustainability-Aware Performance Index for Cell and Nucleus Instance Segmentation

arXiv:2610.10324v1 Announce Type: new Abstract: Pretrained models for cell and nuclear instance segmentation differ substantially in architecture, pretraining data and objectives, parameter count, inf

Phoneme-Guided Initialization for LLM-based Speech Recognition

arXiv:2610.08994v1 Announce Type: cross Abstract: Speech large language models (speech LLMs) perform well on automatic speech recognition (ASR) when sufficient paired speech-text data is available, bu

researcharxiv-cs-cl

PhyDiCT: Plug-and-Play CT Reconstruction from Sparse X-Rays via Differentiable Rendering and Strong Priors

arXiv:2610.09253v1 Announce Type: new Abstract: Reconstructing 3D Computed Tomography (CT) images from a few X-ray projections is a highly ill-posed inverse problem due to the loss of volumetric infor

Policy Learning with Weak Signals

arXiv:2610.10167v1 Announce Type: cross Abstract: Policy learning in digital experimentation faces three challenges: weak signal-to-noise ratios, rich covariate spaces, and massive data volumes. We fo

safetyarxiv-cs-lg

Position Forcing: Self-Conditioning 3D Generation

arXiv:2610.10342v1 Announce Type: new Abstract: Recent single-stage 3D generative models commonly adopt VecSet representations, encoding 3D shapes as unordered sets of latent tokens. However, compared

researcharxiv-cs-cv

PrismSSL: One Interface, Many Modalities; A Single-Interface Library for Multimodal Self-Supervised Learning

model-releasesarxiv-cs-lg

arXiv:2511.17776v2 Announce Type: replace Abstract: We present PrismSSL, a Python library that unifies state-of-the-art self-supervised learning (SSL) methods across audio, vision, graphs, and cross-m

Agents

Progress and Prospect of AI in ARPES Workflow

arXiv:2610.10140v1 Announce Type: cross Abstract: Artificial intelligence (AI) is becoming an increasingly useful tool across the experimental sciences, including angle-resolved photoemission spectros

agentsarxiv-cs-lg

ProtocolMatch: Protocol-Dependent Model Selection for Scientific Dynamics Forecasting

arXiv:2610.10239v1 Announce Type: new Abstract: Scientific dynamics forecasting is often framed as an architecture choice, although deployment is also determined by observed history, rollout feedback,

local-aiarxiv-cs-lg

QuanLing: Cross-Branch Validation of Language Distance Quantification on Western Romance

arXiv:2610.08851v1 Announce Type: new Abstract: Quantifying language distance among closely related languages remains a core challenge in quantitative linguistics. Our previous work [1] introduced Qua

researcharxiv-cs-cl

RACER: Reflective Agent Coupling Query Interpretation and Tool-Based Retrieval for Frame Selection in Long Video Understanding

arXiv:2610.08954v1 Announce Type: new Abstract: Video large language models (Vid-LLMs) excel at diverse video-language tasks by reasoning over selected frames. However, frame selection for long videos

local-aiarxiv-cs-cv

RDGSplat: Render-Dedicated Geometry for Novel View Synthesis

arXiv:2610.09173v1 Announce Type: new Abstract: 3D foundation models enable efficient novel view synthesis by carrying a Gaussian head on the representation they already use for reconstruction. Howeve

researcharxiv-cs-cv

Hardware

RealtimeWAM: How Fast Can I Run My World Action Model?

arXiv:2610.10079v1 Announce Type: new Abstract: World Action Models (WAMs) combine visual dynamics modeling with action generation, but their high inference latency limits responsive robot control. Re

hardwarearxiv-cs-ro

Relational Abstractions for Spatial Reasoning with Diffusion Models

arXiv:2610.09780v1 Announce Type: new Abstract: Diffusion models excel at image synthesis, but they remain limited in their ability to reliably satisfy structured spatial reasoning constraints. In con

Research on Deep Learning-Based Semantic Segmentation Algorithms for Subcortical Brain Structures

arXiv:1907.09194v3 Announce Type: replace-cross Abstract: Segmentation of subcortical brain structures is fundamental to computer-aided diagnosis and treatment in neurology and related clinical fields

RoboPilot: Generalizable Dynamic Robotic Manipulation with Dual-thinking Modes

model-releasesarxiv-cs-ro

arXiv:2510.00154v2 Announce Type: replace Abstract: Despite rapid progress in robotics, complex or long-horizon tasks remain a fundamental challenge. Most current approaches follow an open-loop paradi

RoboRender: Robot-Oriented Video Generation for Visual Sim-to-Real Transfer

arXiv:2610.09254v1 Announce Type: new Abstract: Simulation enables large-scale, low-cost robot data generation, but policies trained in simulation often fail to transfer to the real world due to the s

safetyarxiv-cs-ro

RobotAPO: Adversarial Physics Preference Optimization for Robotic Manipulation Video Generation

arXiv:2610.09454v1 Announce Type: new Abstract: Robotic manipulation videos are increasingly used as visual plans for embodied agents, but optimizing purely for visual plausibility often fails to capt

local-aiarxiv-cs-ro

Robotic Boomerang Throwing via Model-Based Release Design

model-releasesarxiv-cs-ro

arXiv:2610.10472v1 Announce Type: new Abstract: Throwing objects that generate aerodynamic lift can greatly extend robot throwing beyond ballistic flight. A returning boomerang is a challenging exampl

Robotic Ultra-Long-Horizon Manipulation Skills via Human-guided Lifelong Code Generation

arXiv:2509.18597v3 Announce Type: replace Abstract: Large language models (LLMs) can translate natural-language instructions for robotic manipulation into executable code, but ambiguity, noisy generat

tutorialsarxiv-cs-ro

RollVerify: Bridging Efficiency and Accuracy in Long-Tail Rollout Reinforcement Learning

arXiv:2610.09914v1 Announce Type: new Abstract: Reinforcement learning is crucial for improving large language models' reasoning and generalization. It relies on massive rollouts whose lengths become

safetyarxiv-cs-lg

Route-Verify-Vote: Procedure-Conditioned Self-Consistency for Mixed-Domain Reasoning

arXiv:2610.08814v1 Announce Type: cross Abstract: Compositional generalization remains challenging when language models must combine familiar reasoning operations in unfamiliar ways. The Scenario-Base

Rubric Spans are Label Representations: Joint LLM Encoding for Short Answer Scoring

arXiv:2610.09660v1 Announce Type: new Abstract: Automatic Short Answer Scoring (ASAS) requires models that can score student responses against question-specific criteria while remaining efficient and

RunningTab: Direct Workspace Interaction with Environment-Side Tabs

arXiv:2610.10444v1 Announce Type: cross Abstract: Much knowledge work produces new deliverables from files a workspace already holds, and LLM agents are beginning to take such work over. Through direc

S2Tok: Streaming 3D Gaussian Reconstruction with Persistent Spatial Tokens

arXiv:2610.08978v1 Announce Type: new Abstract: Streaming 3D reconstruction requires more than a sequence of geometric predictions: it requires a persistent scene state that can incorporate new eviden

tutorialsarxiv-cs-cv

SAPS: Shared Autonomy for Policy Steering by Blending Teleoperation with a Pretrained VLA

arXiv:2606.15568v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models perform well in generalist robot manipulation but remain brittle to out-of-distribution perturbations, while ful

safetyarxiv-cs-ro

SEER: Self-Enhancing Chain-of-Thought Compression for Reasoning Models

arXiv:2509.14093v3 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting can substantially improve the reasoning ability of large language models (LLMs), but it often comes with high