Search: “models”

CoLA: Multi-VLA Coordination via Learned Adapters

arXiv:2610.15337v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are typically deployed as isolated single-agent policies. When several such agents share a workspace, they can coo

Compute-optimal data scaling for neural surrogates via multi-fidelity training

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DGX agent

arXiv:2610.17221v1 Announce Type: new Abstract: Neural surrogates for Partial Differential Equations (PDEs) are usually trained on synthetic data from numerical simulators. As models grow and scaling

researcharxiv-cs-lg

14 Oct 2026

CrossPortrait: Cross-Species Portrait Animation via Adversarial Motion Alignment

arXiv:2610.17532v1 Announce Type: new Abstract: Cross-species portrait animation, which aims to animate a source portrait of species A using a driving video of species B, is particularly challenging d

Deep Learning and Elicitability for McKean-Vlasov FBSDEs With Common Noise

arXiv:2512.14967v3 Announce Type: replace Abstract: We present a novel numerical method for solving McKean-Vlasov forward-backward stochastic differential equations (MV--FBSDEs) with common noise, com

Degrees of Freedom in Multi-Agent Coordination: Between Centralized and Decentralized Regimes

arXiv:2610.17751v1 Announce Type: cross Abstract: Large language model (LLM)-based multi-agent systems (MAS) are commonly organized around two coordination regimes. Centralized coordination provides e

local-aiarxiv-cs-lg

Applications

Deterministic Prediction as Global Velocity: Flow Matching for Probabilistic Time-Series Forecast

arXiv:2610.18621v1 Announce Type: new Abstract: Accurate uncertainty quantification is critical for many time series forecasting applications, and recent studies have increasingly adopted generative m

applicationsarxiv-cs-lg

Dissecting the Carbon-SLO Tension in Geo-Distributed LLM Serving

arXiv:2610.14571v1 Announce Type: cross Abstract: Large Language Model (LLM) inference is driving a growing share of datacenter carbon emissions. Although carbon-aware scheduling can reduce these emis

safetyarxiv-cs-lg

DR-VLA: Learning Human-Like Quadruped Navigation from Egocentric Web Videos via Domain-Invariant Scene Representations

arXiv:2610.18373v1 Announce Type: new Abstract: Quadruped robots performing outdoor deliveries must interpret complex scenes, anticipate changes, and navigate in socially compliant ways. Robot demonst

Early Detection of Pension-Sponsor Distress from Public Filings: A Sponsor Vulnerability Index, Stress-Augmented VaR, and Dynamic Self-Investment Caps

arXiv:2610.14120v1 Announce Type: cross Abstract: A defined-benefit pension is only as safe as its sponsor, yet sponsor distress is under-instrumented relative to plan-side modelling. We present a tra

ECG-RSI: Recursive Self-Improvement through Targeted Electrocardiogram Waveform Evolution

arXiv:2610.17718v1 Announce Type: cross Abstract: Electrocardiogram (ECG) models need supervision that targets evolving weaknesses and remains faithful to waveform evidence. We introduce ECG-RSI, a re

tutorialsarxiv-cs-lg

Efficient Multi-Agent Reasoning via Confidence-Guided Adaptive Debate

arXiv:2610.16343v1 Announce Type: cross Abstract: Multi-agent debate has shown promise for improving the reasoning of large language models, yet recent theory suggests its benefits are highly regime-d

ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark

arXiv:2512.01495v3 Announce Type: replace Abstract: Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other

Enhanced Trading Systems with Intelligent Market Analysis

arXiv:2610.13998v1 Announce Type: new Abstract: This paper proposes a hybrid reinforcement learning trading framework integrating intraday market data with transformer-based financial sentiment signal

Euclidean Distance-Based Flow Matching

arXiv:2610.18534v1 Announce Type: new Abstract: Flow Matching has recently become popular as a technique for generative modeling with applications in many domains. In the standard Flow Matching formul

Fast Quantized Johnson-Lindenstrauss Transforms

arXiv:2610.16289v1 Announce Type: new Abstract: Quantization has emerged as one of the primary techniques for reducing the memory footprint of large language models during inference. A prominent examp

Applications

Few-for-Many Best-Arm Identification in Multi-Objective Bandits

arXiv:2610.16840v1 Announce Type: new Abstract: Real-world systems often serve many objectives but can deploy only a few options, whose performance must be learned from noisy feedback. Modeling each o

applicationsarxiv-cs-lg

Hardware

FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention

arXiv:2610.17901v1 Announce Type: new Abstract: Long-context training of large language and multimodal models couples structured attention masks (document, prefix-LM, share-question, sliding-window, b

hardwarearxiv-cs-lg

FlowCred: Hierarchical Credit Assignment and Functional Coordination for Joint Text-to-Video Post-Training

arXiv:2610.18142v1 Announce Type: new Abstract: Prompt optimization and generator post-training are two complementary ways to improve text-to-video (T2V) generation, and recent systems increasingly tr

local-aiarxiv-cs-cv

Focus on What You Need: Global-to-Local Dynamic Attention for Multimodal Sarcasm Detection

arXiv:2610.17707v1 Announce Type: new Abstract: Multimodal sarcasm detection has attracted increasing attention due to the widespread use of images and text on social media platforms. Existing studies

local-aiarxiv-cs-lg

Hardware

FORGE: Procedural Weight Generation for Sparse MoE Inference

arXiv:2610.16890v1 Announce Type: cross Abstract: We introduce FORGE (Fast On-chip Rotor Generation for Experts), a procedural weight generation system for Sparse Mixture-of-Experts (MoE) inference. R

hardwarearxiv-cs-lg

FreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation

arXiv:2610.17191v1 Announce Type: new Abstract: Linear-time sequence models typically store long-context information in a recurrent state. A fixed-size state limits how much information can be stored,

From hyperplanes to hyperellipsoids: a pedagogical bridge from linear classifiers to single-qubit mixed-state classifiers

arXiv:2607.15433v2 Announce Type: replace Abstract: Quantum machine learning ideas are typically absent from traditional machine learning curricula and are instead introduced in upper-level courses on

From Transfer Probes to Expert Grouping: Evidence from LoRA Post-Training

arXiv:2610.14437v1 Announce Type: new Abstract: A platform that post-trains one base model for many business lines often has more lines than experts it can maintain, so lines must share experts, yet l

Geometry-Guided Semantic Reconstruction for 3D Instance Segmentation

arXiv:2610.16122v1 Announce Type: new Abstract: 3D instance segmentation requires representations that are both geometrically structured and semantically discriminative. Pure 3D encoders model spatial

GHOST: Geometry-Constrained Hybrid Diffusion for Open-Vocabulary 3D Scene Graph Generation

arXiv:2610.16455v1 Announce Type: new Abstract: 3D scene graph generation requires understanding both object semantics and metric spatial relations. However, existing open-vocabulary methods often str

tutorialsarxiv-cs-cv

Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks - the GATTACA Framework

arXiv:2505.02712v4 Announce Type: replace Abstract: Cellular reprogramming, the artificial transformation of one cell type into another, has been attracting increasing research attention due to its th

Hallucination-aware Faithful Reasoning in Remote Sensing

arXiv:2610.18369v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated promising capabilities for remote sensing reasoning, yet they frequently generate visually un

Hardware-Friendly Token-Group Activation Quantization for Low-Bit Mamba Super-Resolution

arXiv:2610.16261v1 Announce Type: cross Abstract: Mamba-based super-resolution models are efficient alternatives to Transformer-based restoration backbones, but their low-bit post-training quantizatio

Have You Seen It Clearly? Uncertainty-Guided Belief Refinement for Zero-Shot Object Navigation

arXiv:2610.15375v1 Announce Type: new Abstract: Zero-Shot Object Navigation (ZSON) requires an agent to locate target objects in unfamiliar environments without additional training for the test catego

agentsarxiv-cs-ro

Human Pose Estimation by Probabilistic Mixtures of Gaussian and Uniform Distributions

arXiv:2610.14093v1 Announce Type: new Abstract: Despite advancements in sub-pixel decoding, modern Human Pose Estimation (HPE) architectures remain constrained by deterministic coordinate extraction f

Imitation Learning via Discrete and Rhythmic Primitive Composition

arXiv:2610.15639v1 Announce Type: new Abstract: Long-horizon robotic manipulation is inherently composed of semantically meaningful sub-tasks. While Movement Primitives (MPs) can model these component

Imperfect Verifiers, Exact Targets: Inference-Time Scaling for Continuous Generation

arXiv:2610.15281v1 Announce Type: new Abstract: Verifier-guided inference-time scaling uses additional computation to score intermediate states and steer generation toward better outputs. However, imp

Implicit and explicit reparameterizations of the Folded Normal and Rice distributions

arXiv:2610.17151v1 Announce Type: cross Abstract: Variational inference is a flexible tool for modeling experimental data and has proven useful in crystallography. Pathwise gradient estimators provide

Interaction Latents as Actions for Contact-Rich Manipulation

arXiv:2610.18855v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to coordinate not only where to move, but also how contact and force should evolve throughout an interaction.

Applications

Is Complex Query Answering Really Complex?

arXiv:2410.12537v4 Announce Type: replace Abstract: Complex query answering (CQA) on knowledge graphs (KGs) is gaining momentum as a challenging reasoning task. In this paper, we show that the current

applicationsarxiv-cs-lg

Know Yourself and Know Your Neighbour: A Syntactically Informed Self-Supervised Compositional Sentence Representation Learning Framework using a Recursive Hypernetwork

arXiv:2610.16547v1 Announce Type: cross Abstract: Sentence representation learning is still an open challenge in Natural Language Processing. In this work, we propose a new self-supervised framework f

LeanPRM: Lean-Grounded Process Supervision for Natural Language Proof Verification

arXiv:2610.17697v1 Announce Type: new Abstract: AI systems now write long and difficult mathematical proofs, and checking their step-by-step validity is becoming a bottleneck. A learned verifier could

tutorialsarxiv-cs-lg

Learning to Assist: Collaborative VLAs for Implicit Human-Robot Collaboration

arXiv:2606.12475v2 Announce Type: replace Abstract: Human-robot collaboration (HRC) combines the complementary strengths of humans and robots to improve task efficiency. However, many existing collabo

Learning to Design SR Solvers: Harness Optimization for Symbolic Regression

arXiv:2610.16966v1 Announce Type: new Abstract: Symbolic regression (SR) seeks explicit equations that explain observed data, and recent methods increasingly employ large language models (LLMs) and ag

Learning to See through Action: Predictive Curiosity for Robots

arXiv:2610.14302v1 Announce Type: new Abstract: Humans and animals do not learn vision from a fixed set of data: they move, interact, and learn from the visual consequences of their actions. Motivated

safetyarxiv-cs-lg

Less Noise, Same Certificate: Retain Sensitivity for Unlearning

arXiv:2603.03172v2 Announce Type: replace Abstract: Certified machine unlearning aims to provably remove the influence of a deletion set U from a model trained on a dataset S, by producing an unlearne

LiFUSE: Frequency-Spatial Unified Self-Supervised Pretraining for Liver Disease Analysis on Non-contrast CT

arXiv:2610.18243v1 Announce Type: new Abstract: Given the growing global burden of liver tumors and diffuse liver diseases, non-contrast computed tomography (NCCT) is increasingly used for opportunist

LLM-based User-Product Relevance Evaluation for Dynamic Product Advertising

arXiv:2610.14550v1 Announce Type: cross Abstract: Dynamic Product Advertising (DPA) retrieval systems are a core component of modern e-commerce advertising; however, their evaluation remains challengi

Manifold Navigation Learning Using Recurrent Networks: Efficient Training Techniques

arXiv:2610.14325v1 Announce Type: new Abstract: Position tracking is a well-studied problem in Euclidean navigation, yet comparatively little attention has been given to navigation on general manifold

tutorialsarxiv-cs-cv

MemoryVLN: From Ego-Aware Memory Representation to Cross-Context Memory Reuse in Vision-Language Navigation

arXiv:2610.18478v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have shown strong potential for embodied vision-language navigation (VLN), yet their performance degrades on long-h

MFG: Multi-turn Feedback Guided Molecular Optimization

arXiv:2610.18851v1 Announce Type: cross Abstract: Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple

MFlowHOI: Whole-Body Human-Object Interaction Generation via Part-Aware MeanFlow

arXiv:2610.16252v1 Announce Type: new Abstract: Whole-body human-object interaction (HOI) generation requires coordinating body and finger motion, object trajectories, and time-varying contacts. Exist

local-aiarxiv-cs-cv

MicroCLIP: Connecting Text and Microscopy Images via Contrastive Language--Image Pretraining

arXiv:2610.17866v1 Announce Type: new Abstract: Understanding fluorescence microscopy images is fundamental to automating biological research. However, existing methods typically learn predefined conc