Search: “models”

Adaptive Sampling and Clipping for Private Worst-Case Group Optimization

arXiv:2602.10820v2 Announce Type: replace Abstract: A central requirement for the acceptance of machine learning methods for human-centric tasks is that they should be fair, in the sense that they sho

tutorialsarxiv-cs-lg

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Research

Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction

DGX agent

arXiv:2605.28397v1 Announce Type: new Abstract: Predicting conversion from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) is critical for early intervention. Current deep learning paradig

researcharxiv-cs-cv

28 May 2026

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients

arXiv:2605.27412v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have emerged with promising energy-efficient property, yet a substantial performance gap persists compared to Artificia

Agentic Language-to-Objective Synthesis for Optofluidic Assembly

arXiv:2605.27643v1 Announce Type: new Abstract: Light-based advanced manufacturing increasingly requires programmable, closed-loop tools that translate human design intent into executable operations a

agentsarxiv-cs-ro

AI Research Agents Narrow Scientific Exploration

arXiv:2605.27905v1 Announce Type: new Abstract: AI research agents can now generate research ideas, design experiments, run code, and draft papers, raising the possibility of large-scale AI-assisted s

agentsarxiv-cs-cl

AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering?

arXiv:2605.28255v1 Announce Type: new Abstract: AI systems are fallible, and humans can make mistakes in deciding whether to trust AI over their own judgment. Thus, improving human-AI collaboration re

An Empirical Study on Variance-based MC Dropout Uncertainty-Error Correlation in 2D Brain Tumor Segmentation

arXiv:2510.15541v2 Announce Type: replace-cross Abstract: Accurate brain tumor segmentation from MRI is vital for diagnosis and treatment planning. Although Monte Carlo (MC) Dropout is widely used to

researcharxiv-cs-cv

Artemis: Structured Visual Reasoning for Perception Policy Learning

arXiv:2512.01988v2 Announce Type: replace Abstract: Recent reinforcement-learning frameworks for visual perception policy usually incorporate intermediate reasoning chains expressed in natural languag

safetyarxiv-cs-cv

Tools

As agents use more context, input tokens have become the majority of price-equivalent token costs.

As AI agents handle increasingly complex tasks with extended context windows, the cost structure of LLM usage has shifted such that input tokens now represent the majority of price-equivalent expenses

toolscursor--x

Attention Projection Mixing with Exogenous Anchors

arXiv:2601.08131v4 Announce Type: replace Abstract: Cross-layer reuse of early attention projections can improve optimization and data efficiency, but it creates a structural conflict: the first layer

researcharxiv-cs-cl

Automate AML alert triage with Amazon Quick and Snowflake Cortex AI

This post demonstrates that integration in action by automating one of the most labor-intensive workflows in financial services: anti-money laundering (AML) alert triage. You will build a triage workf

agentsaws-ml-blog

Local Ai

b9381

local-aillama-cpp-releases

B9381 is a build/release tag for llama.cpp, a C/C++ framework for LLM inference. This release likely includes bug fixes, performance optimizations, and feature improvements to the project, which enabl

Local Ai

b9382

local-aillama-cpp-releases

I don't have specific information about release b9382 from llama.cpp. Based on the GitHub release tag format, this entry likely documents a specific build or commit version of llama.cpp, which is a C+

Banger paper from Harvard. AutoScientists drops the central planner entirely. Agents interpret shared experimental data, self-organize aroun…

Banger paper from Harvard. AutoScientists drops the central planner entirely. Agents interpret shared experimental data, self-organize around promising directions, evaluate proposals before resource a

tutorialsdair-ai--x

BiasEdit: A Training-Free Bias-Detect-and-Edit Framework for Learning Fair Visual Classifiers

arXiv:2605.28450v1 Announce Type: cross Abstract: Visual data from the Web power image classifiers, which often underpin many web services, such as recommendation and content moderation. However, the

CALM-IT: Generating Realistic Long-Form Motivational Interviewing Dialogues with Dual-Actor Conversational Dynamics Tracking

arXiv:2601.10085v2 Announce Type: replace Abstract: Therapeutic dialogue is not a sequence of isolated responses: client goals, motivation, resistance, and therapeutic alliance evolve over time. Yet c

researcharxiv-cs-cl

CircuitLM: A Multi-Agent LLM-Aided Design Framework for Generating Circuit Schematics from Natural Language Prompts

arXiv:2601.04505v3 Announce Type: replace Abstract: Generating accurate circuit schematics from high-level natural language descriptions remains a persistent challenge in electronic design automation

CLEAR-NeRF: Collinearity and Local-region Enhanced Accurate 3D Reconstruction in Unbounded Scenes

arXiv:2605.28125v1 Announce Type: new Abstract: Many real-world 3D reconstruction applications demand photorealism and metric accuracy across unbounded, complex scenes with challenging lighting and im

tutorialsarxiv-cs-cv

CodeGENCAT: Generative Computerized Adaptive Testing for Open-ended Coding Problems

arXiv:2602.20020v2 Announce Type: replace Abstract: Existing Computerized Adaptive Testing (CAT) frameworks typically select questions based on the predicted likelihood that the student will answer co

safetyarxiv-cs-cl

Colosseum: Auditing Collusion in Cooperative Multi-Agent Systems

arXiv:2602.15198v2 Announce Type: replace-cross Abstract: Multi-agent systems, where LLM agents communicate through free-form language, enable sophisticated coordination for solving complex cooperativ

Comonadic Morphophonology: A Compositional Framework for Context-Dependent Morphological Rules in Finnish

arXiv:2605.28484v1 Announce Type: new Abstract: Composing finite-state transducers (FSTs) for context-dependent morphophonological rules -- consonant gradation, vowel harmony, possessive suffix assimi

researcharxiv-cs-cl

Applications

Conveyance: A Versatile Framework for Learning in Structured Class Spaces

arXiv:2605.28420v1 Announce Type: new Abstract: While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-ag

applicationsarxiv-cs-lg

Cross-Modal Action Recognition in Egocentric Video Using Mamba: Integrating RGB and Hand Skeleton Streams via CLS Token Fusion Strategies

arXiv:2605.24302v2 Announce Type: replace Abstract: Egocentric action recognition is a challenging task due to erratic camera motion, frequent hand occlusion, and the difficulty of maintaining consist

researcharxiv-cs-cv

CubePart: An Open-Vocabulary Part-Controllable 3D Generator

arXiv:2605.28763v1 Announce Type: new Abstract: Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted beh

Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention

arXiv:2605.27584v1 Announce Type: new Abstract: The proliferation of social media platforms and online communities has inadvertently catalyzed the spread of cyberbullying, hate speech, and other forms

D^2Turb: Depth-Aware Simulation and Decoupled Learning for Single-Frame Atmospheric Turbulence Mitigation

arXiv:2605.27460v1 Announce Type: new Abstract: Single-frame atmospheric turbulence mitigation is inherently ill-posed due to spatially varying blur coupled with non-rigid geometric distortion. Existi

tutorialsarxiv-cs-cv

Deconstructing Spatial Complexity: Hierarchical Decomposition for LLM Spatial Reasoning

arXiv:2605.28144v1 Announce Type: new Abstract: LLMs have shown remarkable proficiency in general language understanding and reasoning. However, they consistently underperform in spatial reasoning tha

Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization

arXiv:2602.06880v2 Announce Type: replace Abstract: Adaptive methods like Adam have become the extit{de facto} standard for large-scale vector and Euclidean optimization due to their coordinate-wise a

Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?

arXiv:2605.28697v1 Announce Type: cross Abstract: Speckle tracking echocardiography (STE) is the clinical standard for myocardial strain estimation. Despite good performance on global strain (GLS), it

Deep Neural Network Training as Random Effects: An Optimization-Inference Duality

arXiv:2605.27991v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have achieved remarkable empirical success, yet their training dynamics remain understood mainly from optimization rather

Delay-Aware Reinforcement Learning for Highway On-Ramp Merging under Stochastic Communication Latency

arXiv:2403.11852v5 Announce Type: replace-cross Abstract: Delayed and partially observable state information poses significant challenges for reinforcement learning (RL)-based control in real-world au

DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation

arXiv:2605.27931v1 Announce Type: new Abstract: Scientific diagrams are essential for communicating complex methodologies in academic papers. A natural way for researchers to specify such diagrams is

tutorialsarxiv-cs-ai

DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing

arXiv:2605.28491v1 Announce Type: new Abstract: We study real-time audio-responsive character control as a deployment-faithful problem: strictly causal, bounded-latency streaming that must generate co

safetyarxiv-cs-cv

Discovery Agents for Real-Time Analytics: Toward Proactive Insight Systems

arXiv:2605.27571v1 Announce Type: new Abstract: Modern analytics systems are fundamentally reactive, requiring users to define queries over increasingly complex and continuously evolving data. In real

Do Agents Know What They Can't Do? Evaluating Feasibility Awareness in Tool-Using Agents

arXiv:2605.28532v1 Announce Type: new Abstract: Tool-using agents often incur substantial computational cost due to long reasoning chains and iterative tool usage. In practical scenarios, many tasks b

Do Agents Need Semantic Metadata? A Comparative Study in Agentic Data Retrieval

arXiv:2605.28787v1 Announce Type: cross Abstract: In the era of autonomous agents, machine-actionable data is critical for data-driven workflows. For more than a decade, semantic metadata like schema.

Eliot: Interactively nderline{E}xploring Fast-Changing Scientific nderline{Li}terature Trends with nderline{O}nline Danderline{t}a and Learning

arXiv:2605.27610v1 Announce Type: cross Abstract: The rapid growth of scientific publishing has made it increasingly difficult to track how fast-moving areas evolve. Search engines and LLM-based assis

Examining Agents' Bias Amplification versus Suppression in Multi-Agent Systems

arXiv:2605.28098v1 Announce Type: new Abstract: Multi-agent systems are increasingly deployed to support various tasks where agents interact to achieve individual and collective objectives. Although t

Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations

arXiv:2605.28704v1 Announce Type: new Abstract: Most existing expressivity theories for neural networks assume exact real arithmetic, whereas practical neural networks are executed under finite-precis

Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL

arXiv:2605.28751v1 Announce Type: cross Abstract: Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative w

Applications

Fine-Tuned LLM as a Complementary Predictor Improving Ads System

arXiv:2605.27856v1 Announce Type: cross Abstract: Recommendation systems power engagement and monetization across feeds, ads, and short-video platforms, but translating the latest advances in Large La

applicationsarxiv-cs-ai

FinTexTS: Financial Text-Paired Time-Series Dataset via Semantic-Based and Multi-Level Pairing

arXiv:2603.02702v3 Announce Type: replace Abstract: The financial domain involves a variety of important time-series problems. Recently, time-series analysis methods that jointly leverage textual and

Fitting Unknown Number of Hyperplanes with Manifold Optimization

arXiv:2605.28501v1 Announce Type: new Abstract: Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-d

Applications

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation

arXiv:2605.21832v2 Announce Type: replace Abstract: Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates coll

applicationsarxiv-cs-ai

Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal

arXiv:2605.27919v1 Announce Type: cross Abstract: Learning visuomotor policies via behavior cloning typically involves mimicking expert demonstrations collected by human operators. However, natural hu

From Learning Resources to Competencies: LLM-Based Tagging with Evidence and Graph Constraints

arXiv:2605.28483v1 Announce Type: new Abstract: Linking learning resources to a structured competency framework is key to enabling competency-based search and curriculum analytics in Learning Manageme

From Passive Monitoring to Active Defence: Resilient Control of Manipulators Under Cyberattacks

arXiv:2603.13003v2 Announce Type: replace Abstract: Cyber-physical robotic systems are vulnerable to false data injection attacks (FDIAs), in which an adversary corrupts sensor signals while evading r

researcharxiv-cs-ro

GE-Sim 2.0: A Roadmap Towards Comprehensive Closed-loop Video World Simulators for Robotic Manipulation

arXiv:2605.27491v1 Announce Type: new Abstract: We introduce GE-Sim 2.0 (Genie Envisioner World Simulator 2.0), a closed-loop video world simulator for robotic manipulation. Building on the action-con

safetyarxiv-cs-ro