Search: “papers”

Incast-Free MoE Rate-Based Scheduling

arXiv:2607.26340v1 Announce Type: cross Abstract: Mixture of Experts (MoE) architectures have become key to large language models; however, their typical round-robin (RR) scheduling introduces signifi

Inkling-small. 2 weeks after inkling Nearly as good as Inkling but 4x smaller. We're just getting started...🔥

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

Inkling-small. 2 weeks after inkling Nearly as good as Inkling but 4x smaller. We're just getting started...🔥 Today, we are releasing Inkling-Small. Inkling-Small achieves comparable performance to In

researchsoumith-chintala--x

30 Jul 2026

Invariant Extended Kalman Filtering with Partial Orientation Measurement Integration: Theoretical Derivations and Application to Autonomous Surface Vessels

arXiv:2506.10850v2 Announce Type: replace Abstract: Autonomous surface vessels (ASVs) are increasingly vital for marine science, offering robust platforms for underwater mapping and inspection. Accura

agentsarxiv-cs-ro

JEPADepth: Masked Predictive Representation Learning for Self-Supervised Monocular Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2607.26600v1 Announce Type: new Abstract: Self-supervised monocular depth estimation typically relies on photometric reconstruction losses that couple depth, pose, and appearance assumptions. In

Kairos: Numerically Robust News Recommendation under Item Cold-Start via Cholesky-based LinUCB

arXiv:2607.26832v1 Announce Type: new Abstract: Algorithmic news personalization in regional markets often fails because modern deep learning models require massive interaction data while real-world n

applicationsarxiv-cs-lg

Knowledge-guided Disentanglement with Atomic Actions for Action Recognition

arXiv:2607.26097v1 Announce Type: new Abstract: Action recognition in complex scenes often involves multiple concurrent fine-grained actions, making it challenging to model internal action structures.

LAMUS: A Large-Scale Corpus for Legal Argument Mining from U.S. Caselaw using LLMs

arXiv:2603.08286v2 Announce Type: replace Abstract: Legal argument mining aims to identify and classify the functional components of judicial reasoning, such as facts, issues, rules, analysis, and con

applicationsarxiv-cs-cl

Language Models are not Equally Robust to Non-Canonical Tokenization across Languages

model-releasesarxiv-cs-cl

arXiv:2607.26831v1 Announce Type: new Abstract: Despite the existence of exponentially many valid tokenizations for a given string, language models operate on a single canonical sequence deterministic

Large Emotional World Model

arXiv:2512.24149v2 Announce Type: replace Abstract: The world is governed by both physical laws and affective dynamics. Physical laws govern state transitions, while affective dynamics shape human act

researcharxiv-cs-cl

Learning the Word Problem: Geodesic Lengths and Cryptographic Applications

arXiv:2607.26241v1 Announce Type: cross Abstract: The Word Problem has been a subject of intensive mathematical study for over a century, initially driving advances in combinatorial group theory and m

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities

arXiv:2505.01043v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t

Local Ai

Making a synthetic dataset for fine-tuning

I've been thinking about building a pipeline to generate reasoning training data for LLMs, but I want to avoid the common failure mode of synthetic data where you just generate the same template with

local-air-localllama

Metis: Memory Foundation Model

arXiv:2607.26760v1 Announce Type: new Abstract: Recent advances in AI agents have increasingly internalized native capabilities into their underlying foundation models, giving rise to multimodal found

agentsarxiv-cs-cl

Mitigating Compounding Error via Video Representation Regularization

arXiv:2607.27036v1 Announce Type: new Abstract: Video diffusion-based world models enable long autoregressive video generation for robotics, autonomous driving and simulation tasks, yet sliding-window

agentsarxiv-cs-cv

Mixture-of-experts for handwriting trajectory reconstruction from IMU sensors

model-releasesarxiv-cs-lg

arXiv:2607.26708v1 Announce Type: new Abstract: The use of digital pens for online handwriting trajectory reconstruction is a prevalent method for human-computer interaction. In this study, we focus o

MLVC: Multi-platform Learned Video Codec for Real-World Deployment [P]

applicationsr-machinelearning

I've always found it a little strange that AI is everywhere, but the codecs we use in practice are the traditional hand-engineered systems like h.264, h.265, av1. Alexnet started the wave of neural ne

Neural Network Assisted Lifting Steps For Improved Fully Scalable Lossy Image Compression in JPEG 2000

arXiv:2403.01647v2 Announce Type: replace Abstract: This work proposes to augment the lifting steps of the conventional wavelet transform with additional neural network assisted lifting steps. These a

No Data Is Not No Risk: Visibility Aware Graph-Based Inference of Business Conduct Risk

arXiv:2607.26859v1 Announce Type: cross Abstract: The monitoring of business conduct risk is hindered by sparse, uneven, and visibility-biased data. Prior studies show that business conduct risk infor

Parameterized Fair Resource Allocation under Diversity Constraints

arXiv:2607.26485v1 Announce Type: cross Abstract: Resource allocation across multiple agent groups arises in many applications including e-commerce recommendation systems, housing assignment, and cour

safetyarxiv-cs-lg

Particle-Filtering-based Latent Diffusion for Inverse Problems

arXiv:2408.13868v2 Announce Type: replace Abstract: Current strategies for solving image-based inverse problems apply latent diffusion models to perform posterior sampling.However, almost all approach

PIKS: Universal Physics-Informed Kernel Methods

arXiv:2607.27062v1 Announce Type: cross Abstract: Physics-informed machine learning incorporates physical principles --often expressed via differential operators-- into data-driven models. While physi

Hardware

PolygMap: A Perceptive Locomotion Framework for Humanoid Robot Stair Climbing

arXiv:2510.12346v2 Announce Type: replace Abstract: Recently, biped robot walking technology has been significantly developed, mainly in the context of a bland walking scheme. To emulate human walking

hardwarearxiv-cs-ro

Reinforcement Learning on Cost-Constrained Quadrupedal Hardware

arXiv:2607.26434v1 Announce Type: new Abstract: Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the

researcharxiv-cs-ro

Robostreet Flow: A Lightweight, Ultra-Low-Drag Electric Tractor and Four-Truck Hybrid Convoy Architecture for Minimum-Cost Point-to-Point Freight

arXiv:2607.26250v1 Announce Type: new Abstract: Line-haul trucking costs are dominated by three comparably sized components: energy, driver labor, and equipment. Most efficiency technologies address o

safetyarxiv-cs-cl

Local Ai

ScratchSim: A Procedural Synthetic Data Pipeline for Surface Scratch Detection

arXiv:2607.27065v1 Announce Type: new Abstract: While automated defect detection such as the detection of surface scratched is an important aspect in industrial quality control, the scarcity of annota

local-aiarxiv-cs-cv

Semantic-Aware Temporal Adaptation for UAV Anti-UAV Tracking

model-releasesarxiv-cs-cv

arXiv:2607.26511v1 Announce Type: new Abstract: UAV Anti-UAV tracking is an emerging low-altitude security task for localizing an adversarial UAV using the onboard camera of a moving observer UAV. It

Sim2Win: A Team-Agnostic, Event-Based Pre-Match Outcome Prediction and Tactical Profiling System for Football

arXiv:2607.26061v1 Announce Type: new Abstract: Pre-match tactical decision-making in professional football relies heavily on subjective expert analysis and identity-based scouting systems that cannot

Sky sphere representation in language models

arXiv:2607.27092v1 Announce Type: new Abstract: We analyze whether language models of size ~100B have a representation of the night sky map that is decodable from their residual stream. We find that m

Speech2Grasp: Data-Efficient Transfer of Text-Conditioned Grasp Detection to Speech in Humanoid Robots

arXiv:2607.26567v1 Announce Type: cross Abstract: Humanoid robots increasingly require multi-modal understanding for natural interaction with humans. Despite the prominence of vision-language models,

applicationsarxiv-cs-cv

StatePlay: State-Aware Game World Models for Mechanics-Consistent Generation

arXiv:2607.26754v1 Announce Type: new Abstract: Recent game world models can generate visually realistic and interactive environments conditioned on player actions. However, games are not defined by p

tutorialsarxiv-cs-cv

Symphony of Bias: Exploring Gender Associations with Musical Instruments in Multimodal LLMs

model-releasesarxiv-cs-cl

arXiv:2607.26355v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in everyday life and widely used for information seeking, raising concerns about their potential

Temporally Centered SIGReg Improves Multi-Task LeWorldModel Learning: From Analysis to Method

model-releasesarxiv-cs-lg

arXiv:2607.26924v1 Announce Type: new Abstract: Recent work on LeWorldModel (LeWM) has shown that the Sketched Isotropic Gaussian Regularizer (SIGReg) enables stable end-to-end world-model learning fr

// The agent is its own best speculator // Agents spend a large share of wall-clock time waiting on tool results. Speculation hides that lat…

// The agent is its own best speculator // Agents spend a large share of wall-clock time waiting on tool results. Speculation hides that latency by predicting and pre-executing the next call, but exte

safetydair-ai--x

Time-delay Control Using a New Nonlinear Adaptive Law for Cable-Driven Robots

arXiv:2607.26383v1 Announce Type: cross Abstract: Cable-driven manipulators exhibit strong nonlinearities and low structural stiffness, which make precise control challenging under time-varying uncert

researcharxiv-cs-ro

TPCD: Tone-Pressure Contrastive Decoding and the Label-Free Gating Bottleneck in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2607.26536v1 Announce Type: new Abstract: High-pressure prompts can push vision-language models (VLMs) into unsupported commitments, such as reading illegible text, reporting indeterminate times

Weight and Height Estimation from a Single Human Image Captured in the Wild

arXiv:2607.26104v1 Announce Type: new Abstract: A person's physical characteristics such as weight and height are important indicators of his physical and mental health, daily life routines and financ

A Causality-aware Infer-diagnose-refine Framework for Test-time Modality Adaptation in VLA Models

arXiv:2607.25516v1 Announce Type: new Abstract: Vision-language-action (VLA) models predict sequential actions to execute tasks specified by language instructions, conditioned on visual observations a

tutorialsarxiv-cs-ro

A Functional Approach to Curve Alignment and Shape Analysis

arXiv:2503.05632v2 Announce Type: cross Abstract: In many image analysis problems, the contours of objects carry important statistical information about shape. Such contours are typically affected by

safetyarxiv-cs-cv

A GAN-Based Framework for Robust Data Synthesis in Satellite Internet Observations

arXiv:2607.24790v1 Announce Type: new Abstract: Low-Earth orbit (LEO) satellite Internet has become an important infrastructure for enabling ubiquitous connectivity to align with the International Tel

applicationsarxiv-cs-ai

Agentic inference wastes GPUs on KV cache thrashing. ThunderAgent fixes it at the scheduler level: 2.5x higher single-node throughput and ~1…

Agentic inference wastes GPUs on KV cache thrashing. ThunderAgent fixes it at the scheduler level: 2.5x higher single-node throughput and ~10x lower P50 latency at high concurrency. ThunderAgent was a

agentstogether-ai--x

AI-Assisted Knowledge Access for Legacy Enterprise Asset Management in Energy Operations: A Practical Retrieval System

arXiv:2607.24792v1 Announce Type: cross Abstract: Energy utilities still run engineering work management, engineering procurement, and inventory processes on long-lived enterprise asset management pla

tutorialsarxiv-cs-ai

Aletheia: An Offline-First Clinical Decision Support System for Differential Diagnosis in Low-Resource Healthcare Settings

model-releasesarxiv-cs-ai

arXiv:2607.24814v1 Announce Type: new Abstract: Access to specialist clinical expertise remains severely limited across sub-Saharan Africa, where physician-to-patient ratios can fall below 1:25,000 in

Anti-Backdoor Coreset Selection via Cumulative Entropy

arXiv:2607.25502v1 Announce Type: new Abstract: Recent training-time defenses against neural backdoors isolate a benign subset from poisoned training data, to learn a backdoor-free model from it. In t

tutorialsarxiv-cs-lg

Architectural Backdoors in Vision-Language Model Supply Chains via Representation Steering

arXiv:2607.25479v1 Announce Type: cross Abstract: Vision--Language Models (VLMs) are increasingly deployed through a model supply chain in which pretrained checkpoints, architecture definitions, text

safetyarxiv-cs-ai

Automated Numerical Stability Analysis of Deep Learning Operators

arXiv:2607.25494v1 Announce Type: cross Abstract: Finite-precision arithmetic unavoidably introduces numerical approximation errors. Numerical computations may use insufficient precision or an imprope

researcharxiv-cs-ai

Behavior-Driven Explainability

arXiv:2607.24881v1 Announce Type: new Abstract: As system complexity has vastly increased, it has become significantly more challenging for a single person or a team to fully understand all aspects of

safetyarxiv-cs-lg

Breaking the Periodicity Assumption: Robust Tensorial Multi-View Clustering via Graph-Spectral Low-Rank Learning

arXiv:2607.25295v1 Announce Type: new Abstract: Tensorial multi-view clustering (TMC) has achieved strong performance due to its ability to capture high-order correlations across multiple views. Most

Bumblebee: Interleaved Mixed-Layer Building Blocks for Large-Scale Recommendation Systems

arXiv:2607.24804v1 Announce Type: cross Abstract: Recommendation systems have undergone significant transformations in the past years. The transition from traditional feature interaction modules to ge