Search: “framework”

IceBreaker for Conversational Agents: Breaking the First-Message Barrier with Personalized Starters

arXiv:2604.18375v1 Announce Type: new Abstract: Conversational agents, such as ChatGPT and Doubao, have become essential daily assistants for billions of users. To further enhance engagement, these sy

safetyarxiv-cs-cl

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Model Releases

IDOBE: Infectious Disease Outbreak forecasting Benchmark Ecosystem

DGX agent

arXiv:2604.18521v1 Announce Type: new Abstract: Epidemic forecasting has become an integral part of real-time infectious disease outbreak response. While collaborative ensembles composed of statistica

model-releasesarxiv-cs-lg

21 Apr 2026

Improving LLM Code Reasoning via Semantic Equivalence Self-Play with Formal Verification

model-releasesarxiv-cs-cl

arXiv:2604.17010v1 Announce Type: new Abstract: We introduce a self-play framework for semantic equivalence in Haskell, utilizing formal verification to guide adversarial training between a generator

Learning the Riccati solution operator for time-varying LQR via Deep Operator Networks

arXiv:2604.18507v1 Announce Type: cross Abstract: We propose a computational framework for replacing the repeated numerical solution of differential Riccati equations in finite-horizon Linear Quadrati

LiDAR-based Crowd Navigation with Visible Edge Group Representation

arXiv:2604.16741v1 Announce Type: new Abstract: Robot navigation in crowded pedestrian environments is a well-known challenge and we explore the practical deployment of group-based representations in

LQM: Linguistically Motivated Multidimensional Quality Metrics for Machine Translation

arXiv:2604.18490v1 Announce Type: new Abstract: Existing MT evaluation frameworks, including automatic metrics and human evaluation schemes such as Multidimensional Quality Metrics (MQM), are largely

researcharxiv-cs-cl

PowerCLIP: Powerset Alignment for Contrastive Pre-Training

arXiv:2511.23170v5 Announce Type: replace Abstract: Contrastive vision-language pre-training frameworks such as CLIP have demonstrated impressive zero-shot performance across a range of vision-languag

safetyarxiv-cs-cv

RefineStat: Efficient Exploration for Probabilistic Program Synthesis

arXiv:2509.01082v3 Announce Type: replace Abstract: Probabilistic programming offers a powerful framework for modeling uncertainty, yet statistical model discovery in this domain entails navigating an

Sampling for Quality: Training-Free Reward-Guided LLM Decoding via Sequential Monte Carlo

arXiv:2604.16453v1 Announce Type: new Abstract: We introduce a principled probabilistic framework for reward-guided decoding in large language models, addressing the limitations of standard decoding m

Hardware

Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs

arXiv:2604.16715v1 Announce Type: cross Abstract: Graph foundation models have demonstrated remarkable adaptability across diverse downstream tasks through large-scale pretraining on graphs. However,

hardwarearxiv-cs-lg

Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems

arXiv:2604.18438v1 Announce Type: new Abstract: We present a scalable, data-driven simulation framework for large-scale heating, ventilation, and air conditioning (HVAC) systems that couples physics-i

safetyarxiv-cs-lg

Local Ai

SignDPO: Multi-level Direct Preference Optimisation for Skeleton-based Gloss-free Sign Language Translation

arXiv:2604.18034v1 Announce Type: new Abstract: We present SignDPO, a novel multi-level Direct Preference Optimisation (DPO) framework designed to enhance the alignment of skeleton-based Sign Language

local-aiarxiv-cs-cl

StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation

arXiv:2601.04740v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly applied in specialized domains such as finance and healthcare, where they introduce unique safety risk

safetyarxiv-cs-cl

STL-Based Motion Planning and Uncertainty-Aware Risk Analysis for Human-Robot Collaboration with a Multi-Rotor Aerial Vehicle

arXiv:2509.10692v3 Announce Type: replace Abstract: This paper presents a motion planning and risk analysis framework for enhancing human-robot collaboration with a Multi-Rotor Aerial Vehicle. The pro

Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Models

arXiv:2604.18107v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) achieve remarkable performance in sequential decision-making but remain fragile to subtle environmental shifts, suc

The Collaboration Gap in Human-AI Work

arXiv:2604.18096v1 Announce Type: cross Abstract: LLMs are increasingly presented as collaborators in programming, design, writing, and analysis. Yet the practical experience of working with them ofte

Think before Go: Hierarchical Reasoning for Image-goal Navigation

arXiv:2604.17407v1 Announce Type: new Abstract: Image-goal navigation steers an agent to a target location specified by an image in unseen environments. Existing methods primarily handle this task by

Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles

arXiv:2604.17156v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a promising framework for solving inverse problems governed by partial differential equations (

Tutorials

Unraveling the Key of Machine Learning-based Android Malware Detection

arXiv:2402.02953v2 Announce Type: replace-cross Abstract: With the rapid advancement of machine learning (ML), ML-based Android malware detection has gained significant popularity due to its ability t

tutorialsarxiv-cs-lg

VIDEOP2R: Video Understanding from Perception to Reasoning

arXiv:2511.11113v2 Announce Type: replace Abstract: Reinforcement fine-tuning (RFT), a two-stage framework consisting of supervised fine-tuning (SFT) and reinforcement learning (RL) has shown promisin

safetyarxiv-cs-cv

ViT^3: Unlocking Test-Time Training in Vision

arXiv:2512.01643v2 Announce Type: replace Abstract: Test-Time Training (TTT) has recently emerged as a promising direction for efficient sequence modeling. TTT reformulates attention operation as an o

AST: Adaptive, Seamless, and Training-Free Precise Speech Editing

arXiv:2604.16056v1 Announce Type: cross Abstract: Text-based speech editing aims to modify specific segments while preserving speaker identity and acoustic context. Existing methods rely on task-speci

researcharxiv-cs-ai

AutoFed: Personalized Federated Traffic Prediction via Adaptive Prompt

model-releasesarxiv-cs-ai

arXiv:2512.24625v2 Announce Type: replace-cross Abstract: Accurate traffic prediction is essential for Intelligent Transportation Systems, including ride-hailing, urban road planning, and vehicle flee

Agents

Evaluating LLM Simulators as Differentially Private Data Generators

arXiv:2604.15461v1 Announce Type: cross Abstract: LLM-based simulators offer a promising path for generating complex synthetic data where traditional differentially private (DP) methods struggle with

agentsarxiv-cs-cl

Frequency-Aware Flow Matching for High-Quality Image Generation

model-releasesarxiv-cs-cv

arXiv:2604.15521v1 Announce Type: new Abstract: Flow matching models have emerged as a powerful framework for realistic image generation by learning to reverse a corruption process that progressively

HiPreNets: High-Precision Neural Networks through Progressive Training

model-releasesarxiv-cs-lg

arXiv:2506.15064v3 Announce Type: replace Abstract: Deep neural networks are powerful tools for solving nonlinear problems in science and engineering, but training highly accurate models becomes chall

Preference Estimation via Opponent Modeling in Multi-Agent Negotiation

model-releasesarxiv-cs-cl

arXiv:2604.15687v1 Announce Type: new Abstract: Automated negotiation in complex, multi-party and multi-issue settings critically depends on accurate opponent modeling. However, conventional numerical

Safe and Energy-Aware Multi-Robot Density Control via PDE-Constrained Optimization for Long-Duration Autonomy

arXiv:2604.15524v1 Announce Type: cross Abstract: This paper presents a novel density control framework for multi-robot systems with spatial safety and energy sustainability guarantees. Stochastic rob

StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Models

arXiv:2604.15416v1 Announce Type: cross Abstract: Sign-based optimization algorithms, such as SignSGD, have garnered significant attention for their remarkable performance in distributed learning and

researcharxiv-cs-ai

Truncated Kernel Stochastic Gradient Descent with General Losses and Spherical Radial Basis Functions

arXiv:2510.04237v5 Announce Type: replace Abstract: In this paper, we propose a novel kernel stochastic gradient descent (SGD) algorithm for large-scale supervised learning with general losses. Compar

safetyarxiv-cs-lg

When looking at deep learning profiles, one of the most obvious tells between a mediocre and great candidate is whether they list PyTorch or…

researchfrancois-chollet--x

Francois Chollet discusses a hiring signal for identifying high-quality deep learning candidates based on their choice of machine learning frameworks, suggesting PyTorch proficiency (or lack thereof)

18 Apr 2026

Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models

arXiv:2508.15396v2 Announce Type: replace Abstract: The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a grow

researcharxiv-cs-cl

Agents

connect, ingest, extract, enrich

This post likely discusses a four-step framework for data processing and AI workflows: connecting to data sources, ingesting raw data, extracting relevant information, and enriching it with additional

agentsyohei-nakajima--x

Efficient Search of Implantable Adaptive Cells for Medical Image Segmentation

arXiv:2604.14849v1 Announce Type: new Abstract: Purpose: Adaptive skip modules can improve medical image segmentation, but searching for them is computationally costly. Implantable Adaptive Cells (IAC

Expert-Guided Class-Conditional Goodness-of-Fit Scores for Interpretable Classification with Informative Missingness: An Application to Seismic Monitoring

arXiv:2604.14809v1 Announce Type: cross Abstract: We study a classification problem with three key challenges: pervasive informative missingness, the integration of partial prior expert knowledge into

Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure Generation

arXiv:2604.13354v1 Announce Type: cross Abstract: The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially

researcharxiv-cs-ai

Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems

arXiv:2510.14133v2 Announce Type: replace Abstract: Agentic AI systems, which leverage multiple autonomous agents and large language models (LLMs), are increasingly used to address complex, multi-step

safetyarxiv-cs-ai

Giving Faces Their Feelings Back: Explicit Emotion Control for Feedforward Single-Image 3D Head Avatars

arXiv:2604.14541v1 Announce Type: new Abstract: We present a framework for explicit emotion control in feed-forward, single-image 3D head avatar reconstruction. Unlike existing pipelines where emotion

Agents

MCPThreatHive: Automated Threat Intelligence for Model Context Protocol Ecosystems

arXiv:2604.13849v1 Announce Type: cross Abstract: The rapid proliferation of Model Context Protocol (MCP)-based agentic systems has introduced a new category of security threats that existing framewor

agentsarxiv-cs-ai

MedVerse: Efficient and Reliable Medical Reasoning via DAG-Structured Parallel Execution

arXiv:2602.07529v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong performance and rapid progress in a wide range of medical reasoning tasks. However, their sequ

Applications

Model-Based Reinforcement Learning under Random Observation Delays

arXiv:2509.20869v2 Announce Type: replace Abstract: Delays frequently occur in real-world environments, yet standard reinforcement learning (RL) algorithms often assume instantaneous perception of the

applicationsarxiv-cs-lg

Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

arXiv:2604.14206v1 Announce Type: new Abstract: This paper proposes a machine learning assisted portfolio optimization framework designed for low data environments and regime uncertainty. We construct

PUFFIN: Protein Unit Discovery with Functional Supervision

arXiv:2604.14796v1 Announce Type: cross Abstract: Proteins carry out biological functions through the coordinated action of groups of residues organized into structural arrangements. These arrangement

Local Ai

Rethinking AI Hardware: A Three-Layer Cognitive Architecture for Autonomous Agents

arXiv:2604.13757v1 Announce Type: new Abstract: The next generation of autonomous AI systems will be constrained not only by model capability, but by how intelligence is structured across heterogeneou

local-aiarxiv-cs-ai

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization

arXiv:2601.20868v2 Announce Type: replace Abstract: Large Language Models (LLMs) have advanced the field of Combinatorial Optimization through automated heuristic generation. Instead of relying on man

Scouting By Reward: VLM-TO-IRL-Driven Player Selection For Esports

arXiv:2604.14474v1 Announce Type: new Abstract: Traditional esports scouting workflows rely heavily on manual video review and aggregate performance metrics, which often fail to capture the nuanced de

safetyarxiv-cs-lg

Speak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgery

model-releasesarxiv-cs-cv

arXiv:2603.16024v2 Announce Type: replace Abstract: We introduce a speech-guided embodied agent framework for video-guided skull base surgery that dynamically executes perception and image-guidance ta

StreamCacheVGGT: Streaming Visual Geometry Transformers with Robust Scoring and Hybrid Cache Compression

arXiv:2604.15237v1 Announce Type: new Abstract: Reconstructing dense 3D geometry from continuous video streams requires stable inference under a constant memory budget. Existing O(1) frameworks primar