Search: “models”

Meta is offering a cheaper Muse Spark 1.2 'contributor' tier priced at 0.10/1M input and 0.20/1M output tokens in exchange for using user prompts for training (Wall Street Journal)

Wall Street Journal: Meta is offering a cheaper Muse Spark 1.2 “contributor” tier priced at 0.10/1M input and 0.20/1M output tokens in exchange for using user prompts for training — The company, press

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Micro-Segmentation Anomaly Detection in Zero-Trust Software-Defined Network Fabrics

arXiv:2608.02627v1 Announce Type: cross Abstract: Zero Trust Architecture (ZTA) principles need rigorous network segmentation and ongoing verification to reduce implicit trust and lateral threat propa

applicationsarxiv-cs-cv

MSTAR: Multi-Scale Backbone Architecture Search for Timeseries Classification

arXiv:2402.13822v2 Announce Type: replace Abstract: Most of the previous approaches to Time Series Classification (TSC) highlight the significance of receptive fields and frequencies while overlooking

researcharxiv-cs-cv

MuEvo: LLM-Driven Evolution of Multi-Heuristic Ensemble

arXiv:2608.03636v1 Announce Type: cross Abstract: Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optim

Multi-Camera Trajectory Forecasting with Trajectory Tensors

arXiv:2108.04694v2 Announce Type: cross Abstract: We introduce the problem of multi-camera trajectory forecasting (MCTF), which involves predicting the trajectory of a moving object across a network o

Paired Recipient-based Evaluation of Survival Prediction for Deceased Donor Kidney Transplants

arXiv:2608.03017v1 Announce Type: new Abstract: There has been significant interest in using machine learning algorithms to predict kidney transplant outcomes, such as the number of years until a graf

applicationsarxiv-cs-lg

Pivot-Centric Trajectory Prediction: Bridging Long Horizons via Dynamical Guidance

arXiv:2608.03521v1 Announce Type: cross Abstract: Forecasting precise future motion of surrounding agents is essential for reliable autonomous vehicles. However, as the demand for longer prediction ho

local-aiarxiv-cs-ai

PixelUp: Zero-Shot Semantic Feature Upsampling for Fine-Grained Vision Tasks

arXiv:2608.02792v1 Announce Type: new Abstract: Self-supervised Vision Foundation Models (VFMs) have become essential backbones for downstream tasks due to their strong and transferable visual represe

researcharxiv-cs-cv

Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate

arXiv:2412.11257v4 Announce Type: replace-cross Abstract: For many complex simulation tasks spanning areas such as healthcare, engineering, and finance, Monte Carlo (MC) methods are invaluable due to

local-aiarxiv-cs-lg

Residual Flow Matching with Dynamic Cross-Interaction for 3D Multi-Person Motion Prediction

arXiv:2608.03379v1 Announce Type: new Abstract: 3D multi-person motion prediction requires modeling both individual kinematics and inter-person interactions. While Flow Matching is effective for multi

agentsarxiv-cs-cv

Rethinking Modality Reliability in Multimodal Sentiment Analysis with Incomplete Observations

arXiv:2608.03611v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) integrates text, audio, and vision to infer human affect, yet real-world multimodal observations are often incomplet

RoboReact: Agentic Skill Distillation from Generated Egocentric Videos for Generalizable Whole-Body Manipulation

arXiv:2608.03387v1 Announce Type: new Abstract: Humanoid robots have the potential to perform dexterous manipulation in human environments, yet acquiring diverse and generalizable skills remains costl

agentsarxiv-cs-ro

Schedule-Informed Temporal Fusion Forecasting of Hourly Airport Security-Checkpoint Throughput

arXiv:2608.02950v1 Announce Type: new Abstract: Checkpoint staffing requires accurate forecasts of when screening demand will occur, yet flight schedules record departure times rather than passenger a

researcharxiv-cs-lg

SGFormer: Structure-Guided Transformer for Robust Local Feature Matching

arXiv:2608.03423v1 Announce Type: new Abstract: Local feature matching is a fundamental component of photogrammetry, enabling accurate image correspondence critical for tasks such as 3D reconstruction

local-aiarxiv-cs-cv

Tutorials

Sparse Weight Decomposition for Efficient Circuit Extraction

arXiv:2608.03913v1 Announce Type: cross Abstract: Dense pretrained transformers do not naturally expose interpretable units for circuit extraction. Existing approaches obtain such units by learning au

tutorialsarxiv-cs-cl

Speech LLMs in Low-Resource Scenarios: Data Volume Requirements and the Impact of Pretraining on High-Resource Languages

arXiv:2508.05149v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource languages, reaching state-of-the-art perf

StreamDAM: Presence-Aware Memory for Real-Time Streaming Video Object Segmentation

arXiv:2608.03912v1 Announce Type: new Abstract: Quality-tier video object segmentation (VOS) trackers such as DAM4SAM top accuracy leaderboards, but they are measured offline, one frame at a time with

safetyarxiv-cs-cv

Tutorials

TaskPress: Query-Agnostic KV Cache Compression via Task-Guided Pruning

arXiv:2608.03276v1 Announce Type: new Abstract: Long-context inference with large language models is constrained by the linear growth of the key-value cache to sequence length. While pruning offers mi

tutorialsarxiv-cs-ai

Test Time Adaptation Methods for Point Cloud Registration in Laparoscopic Surgery

arXiv:2608.02883v1 Announce Type: new Abstract: 3D point cloud registration in laparoscopic surgery estimates the transformation between an intraoperative organ reconstructed from video and its preope

safetyarxiv-cs-cv

Test-Time Scaling for Safe Text-Guided Image Generation via Intermediate Clean Estimates

arXiv:2608.03284v1 Announce Type: cross Abstract: Ensuring safety and policy compliance in text-to-image diffusion models remains a critical challenge, as benign or adversarial prompts can often elici

The Eloquence team submission for task 1 of MLC-SLM challenge

arXiv:2507.19308v2 Announce Type: replace-cross Abstract: In this paper, we present our studies and experiments carried out for the task 1 of the Challenge and Workshop on Multilingual Conversational

applicationsarxiv-cs-cl

The Evolutionary Origin of Values: implications for AI alignment, sentience and existential risk

arXiv:2608.03361v1 Announce Type: cross Abstract: AI systems based on Large Language Models (LLMs) have prompted fears that they may harbor hidden goals, seek to dominate or eliminate humanity, or eve

The Signal Horizon: Local Blindness and the Contraction of Pauli-Weight Spectra in Noisy Quantum Encodings

arXiv:2602.14735v2 Announce Type: replace-cross Abstract: The performance of quantum classifiers is typically analyzed through global state distinguishability or the trainability of variational models

safetyarxiv-cs-lg

The Transformer Revolution, Part 1: Dynamic Processing through Output- Weight Interconnections

arXiv:2608.03921v1 Announce Type: new Abstract: This paper offers a new interpretation of the Transformer during inference. Against the 'stochastic parrot' view that large language models merely repro

ToolLIFT: Lifting Tool-Specific Trajectories into Function-Level Graphs for Generalizable Tool Planning

arXiv:2608.03468v1 Announce Type: new Abstract: Historical tool-use trajectories provide valuable experience for large language model (LLM) agents to plan and coordinate tool usage. Existing approache

agentsarxiv-cs-ai

Topological Simplification in Predictive Coding Networks

arXiv:2608.02816v1 Announce Type: new Abstract: We study the topology of learned representations in predictive coding networks (PCNs), a neuro-inspired bidirectional architecture, using a quantitative

researcharxiv-cs-lg

Towards Robust Tool Use in Agents via Experience-Driven Adaptive Guidance

arXiv:2608.03403v1 Announce Type: new Abstract: The performance bottleneck of agents is increasingly shifting from model capability to the robustness of their execution processes. Tools play a central

agentsarxiv-cs-ai

Unexpected Crash-Looping of Multi-GPU Box: Caught by Hand-Scrutinized Logs - A Tale of Overridden Keep-Alive Policy and Eviction Thrashing

I've been freelancing for over a decade now, and I can't stress enough the importance of thorough investigation when dealing with strange software behaviors. Recently, I ran into an issue where my mul

local-air-ollama

Unified Visuomotor Targets: Supervising VLAs Beyond Physical Actions

arXiv:2608.03563v1 Announce Type: new Abstract: VLA models are trained to predict robot actions from visual and language observations. This is a natural choice, but it creates a mismatch: VLMs encode

safetyarxiv-cs-ro

UNVaMP: Neural Knowledge Tracing with Variational Regularization of Latent Knowledge Dynamics

arXiv:2608.03811v1 Announce Type: new Abstract: We introduce the Unified Neural Variational Measurement of Proficiency (UNVaMP) architecture, a knowledge tracing method that integrates observed studen

applicationsarxiv-cs-lg

Variational Approximated Restricted Maximum Likelihood Estimation for Spatial Data

arXiv:2604.07635v2 Announce Type: replace-cross Abstract: This research considers a scalable inference for spatial data modeled through Gaussian intrinsic conditional autoregressive (ICAR) structures.

researcharxiv-cs-lg

Very interesting to see @JeffDean's pitch deck. Just look at those open science and engineering problems. Lots to advance there with automat…

Very interesting to see @JeffDean's pitch deck. Just look at those open science and engineering problems. Lots to advance there with automated ML engineering. AI for science and engineering is just ge

researchdair-ai--x

What Language Does and What the Evidence Supports: A Functional Role Taxonomy and Evidence Audit of Language Grounding in Embodied Agents

arXiv:2608.03099v1 Announce Type: new Abstract: Foundation models place language throughout embodied agents, but its presence does not show what it contributes or how well that contribution is grounde

researcharxiv-cs-cl

When and Where to Look: Adaptive Visual Evidence Scheduling for Efficient Long Video Understanding

arXiv:2608.03918v1 Announce Type: cross Abstract: Efficient long-video understanding requires vision--language models (VLMs) to reason over a small number of frames selected as sparse visual evidence.

local-aiarxiv-cs-ai

When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning

arXiv:2608.02940v1 Announce Type: new Abstract: A reproducible compression statistic can still select the wrong candidate. A dense pruning score with 0.906 split-half reliability predicted a 16.1% gai

local-aiarxiv-cs-ai

When Oracle Conditioning Misleads Deployment: Conditioning-Availability Bias in Echocardiographic Segmentation

arXiv:2608.03342v1 Announce Type: cross Abstract: Conditional segmentation models may be trained and evaluated with auxiliary signals cleaner than those available at deployment. We study this protocol

When Teachers Mislead: Spurious-Signal-Aware On-Policy Distillation

arXiv:2608.03632v1 Announce Type: new Abstract: On-Policy distillation (OPD) transfers teacher capabilities by supervising student-sampled trajectories with dense token-level teacher signals. Recent s

3D-CovDiffusion: 3D-Aware Diffusion Policy for Coverage Path Planning

arXiv:2510.03011v2 Announce Type: replace Abstract: Diffusion models have shown strong potential for robot skill learning, yet their role in coverage path planning remains underexplored. In industrial

safetyarxiv-cs-ro

3DZip: Spatial-Aware Feature Diversity-Guided Token Compression for 3D Question Answering

arXiv:2608.01185v1 Announce Type: new Abstract: Recent 3D vision-language models (3D VLMs) construct geometry aware tokens by projecting 2D visual features into world coordinates, enabling spatial rea

researcharxiv-cs-cv

Abstention as an Action Can Kill Both the Reward Gradient and the KL Anchor: Collapse Law and Repair for Error-Penalized Reinforcement Learning

arXiv:2608.00301v1 Announce Type: cross Abstract: Error-penalized scoring rules (+1 for a correct answer, -lambda for a wrong one, 0 for abstaining) are increasingly prescribed against hallucination:

agentsarxiv-cs-cl

Assessing the Impacts of Imperfect Datasets on Client Selections in Federated Learning

arXiv:2608.02250v1 Announce Type: new Abstract: Federated learning (FL) is a popular distributed learning framework where multiple clients perform local training and a server aggregates the locally up

local-aiarxiv-cs-lg

Attend to Your Own Thoughts: Breaking the Barrier for Post-Training Quantization of Reasoning LLMs through the Lens of 1.58-Bit Quantization

arXiv:2608.01078v1 Announce Type: new Abstract: We propose ScaleQ-1.58, a scalable ternary post-training quantization (PTQ) framework for reasoning LLMs. Its core insight stems from an empirical findi

researcharxiv-cs-cl

Benign Overfitting in Linear Classifiers with a Bias Term

arXiv:2511.12840v2 Announce Type: replace-cross Abstract: Overparameterized models often generalize well even when they interpolate noisy training data. This is known as benign overfitting. For linear

safetyarxiv-cs-lg

Breaking the Statistical Similarity Trap in Extreme Convection Detection

arXiv:2509.09195v2 Announce Type: replace-cross Abstract: Current evaluation metrics for deep learning weather models create a 'Statistical Similarity Trap', rewarding blurry predictions while missing

safetyarxiv-cs-cv

Can AI Agents Simulate A/B Test Outcomes? A Validation Framework for Agentic Experimentation

arXiv:2608.02345v1 Announce Type: new Abstract: A/B testing remains the standard for rolling out new features in the technology industry. Each experiment, however, consumes real traffic, engineering e

agentsarxiv-cs-cl

CascadeLUT: Information-Ordered Streaming Inference for Bandwidth-Constrained FPGAs

arXiv:2608.00720v1 Announce Type: cross Abstract: Mapping neural networks to FPGAs enables low-latency, energy-efficient inference, particularly for lookup table (LUT)-based models that eliminate mult

local-aiarxiv-cs-lg

Tutorials

Coverage-Driven Adaptive Keyframe Selection for Video Understanding

arXiv:2608.00714v1 Announce Type: new Abstract: Recent advances in large vision-language models (LVLMs) have enabled long-video understanding and analysis. However, processing the large number of fram

tutorialsarxiv-cs-cv

CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs

arXiv:2608.02578v1 Announce Type: cross Abstract: World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing th

safetyarxiv-cs-lg