Search: “llm”

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing

arXiv:2604.18918v1 Announce Type: cross Abstract: Simulation-based testing of autonomous driving systems (ADS) must uncover realistic and diverse failures in dense, heterogeneous traffic. However, exi

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How conversational analytics removes the BI bottleneck

DGX agent

Conversational analytics, as demonstrated by Databricks' Genie and Lakebase, helps CIOs, CTOs, and CDOs bypass the traditional Business Intelligence (BI) bottleneck. This approach allows enterprises t

industrydatabricks

22 Apr 2026

Tools

https://x.com/tanayj/status/2046733145446502805?s=46

https://x.com/tanayj/status/2046733145446502805?s=46 My read on the structure of this deal: 1. xAI is leveraging Cursor's data / traces to help train a better coding model (both Grok base model and po

toolsswyx--x

Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning

arXiv:2604.18862v1 Announce Type: cross Abstract: Bug reports, encompassing a wide range of bug types, are crucial for maintaining software quality. However, the increasing complexity and volume of bu

applicationsarxiv-cs-ai

Hybrid Architectures for Language Models: Systematic Analysis and Design Insights

arXiv:2510.04800v3 Announce Type: replace Abstract: Recent progress in large language models demonstrates that hybrid architectures--combining self-attention mechanisms with structured state space mod

researcharxiv-cs-cl

InsideOut: Measuring and Mitigating Insider-Outsider Bias in Interview Script Generation

model-releasesarxiv-cs-ai

arXiv:2509.21080v2 Announce Type: replace-cross Abstract: Advancements in Large language models (LLMs) have enabled a variety of downstream applications like story and interview script generation. How

Introducing Gemini Enterprise Agent Platform, powering the next wave of agents

model-releasesgoogle-cloud-ai

In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. We helped solve that with Vertex AI, our trusted

Knowledge-Guided Time-Varying Causal Inference for Arctic Sea Ice Dynamics

arXiv:2601.17647v2 Announce Type: replace-cross Abstract: Quantifying the causal relationship between sea ice thickness and sea surface height (SSH) is essential for understanding the mechanisms drivi

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors

arXiv:2604.19028v1 Announce Type: new Abstract: One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face

applicationsarxiv-cs-lg

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization

arXiv:2506.09373v3 Announce Type: replace-cross Abstract: The advent of autonomous agents is transforming interactions with Graphical User Interfaces (GUIs) by employing natural language as a powerful

Mango: Multi-Agent Web Navigation via Global-View Optimization

model-releasesarxiv-cs-cl

arXiv:2604.18779v1 Announce Type: new Abstract: Existing web agents typically initiate exploration from the root URL, which is inefficient for complex websites with deep hierarchical structures. Witho

Model-Agnostic Meta Learning for Class Imbalance Adaptation

arXiv:2604.18759v1 Announce Type: new Abstract: Class imbalance is a widespread challenge in NLP tasks, significantly hindering robust performance across diverse domains and applications. We introduce

researcharxiv-cs-cl

Tutorials

Modelling and Analysing Behaviours and Emotions via Complex User Interactions

arXiv:1902.07683v1 Announce Type: cross Abstract: Over the past 15 years, the volume, richness and quality of data collected from the combined social networking platforms has increased beyond all expe

tutorialsarxiv-cs-ai

Nexusformer: Nonlinear Attention Expansion for Stable and Inheritable Transformer Scaling

arXiv:2604.19147v1 Announce Type: cross Abstract: Scaling Transformers typically necessitates training larger models from scratch, as standard architectures struggle to expand without discarding learn

researcharxiv-cs-ai

On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation

arXiv:2601.13729v2 Announce Type: replace Abstract: In recent years, the non-deterministic properties of language models have garnered considerable attention and have shown a significant influence on

applicationsarxiv-cs-cl

Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels

arXiv:2506.18186v3 Announce Type: replace Abstract: The restless multi-armed bandit (RMAB) framework is a popular approach to solving resource allocation problems in networked systems. In this paper,

Tutorials

PhysMem: Scaling Test-time Physical Memory for Robot Manipulation

arXiv:2602.20323v5 Announce Type: replace-cross Abstract: Reliable object manipulation requires understanding physical properties that vary across objects and environments. Vision-language model (VLM)

tutorialsarxiv-cs-ai

Plausible Reasoning and First-Order Plausible Logic

arXiv:2604.19036v1 Announce Type: new Abstract: Defeasible statements are statements that are likely, or probable, or usually true, but may occasionally be false. Plausible reasoning makes conclusions

researcharxiv-cs-ai

PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models

arXiv:2604.19684v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) has predominantly focused on generating model-centric explanations that approximate the behavior of black-box

applicationsarxiv-cs-lg

Product-of-Experts Training Reduces Dataset Artifacts in Natural Language Inference

arXiv:2604.19069v1 Announce Type: cross Abstract: Neural NLI models overfit dataset artifacts instead of truly reasoning. A hypothesis-only model gets 57.7% in SNLI, showing strong spurious correlatio

ReflectMT: Internalizing Reflection for Efficient and High-Quality Machine Translation

model-releasesarxiv-cs-cl

arXiv:2604.19144v1 Announce Type: new Abstract: Recent years have witnessed growing interest in applying Large Reasoning Models (LRMs) to Machine Translation (MT). Existing approaches predominantly ad

Regression with Large Language Models for Materials and Molecular Property Prediction

model-releasesarxiv-cs-lg

arXiv:2409.06080v2 Announce Type: replace-cross Abstract: We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviatio

Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients

arXiv:2505.06335v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has the potential for simultaneous global learning amongst a large number of parallel agents, enabling emerging AI suc

Rethinking Information Synthesis in Multimodal Question Answering A Multi-Agent Perspective

arXiv:2505.20816v2 Announce Type: replace Abstract: Recent advances in multimodal question answering have primarily focused on combining heterogeneous modalities or fine-tuning multimodal large langua

agentsarxiv-cs-cl

Revac: A Social Deduction Reasoning Agent

arXiv:2604.19523v1 Announce Type: new Abstract: Social deduction games such as Mafia present a unique AI challenge: players must reason under uncertainty, interpret incomplete and intentionally mislea

Revisiting RaBitQ and TurboQuant: A Symmetric Comparison of Methods, Theory, and Experiments

model-releasesarxiv-cs-ai

arXiv:2604.19528v1 Announce Type: cross Abstract: This technical note revisits the relationship between RaBitQ and TurboQuant under a unified comparison framework. We compare the two methods in terms

Safety-Critical Contextual Control via Online Riemannian Optimization with World Models

arXiv:2604.19639v1 Announce Type: cross Abstract: Modern world models are becoming too complex to admit explicit dynamical descriptions. We study safety-critical contextual control, where a Planner mu

Self-Improving Tabular Language Models via Iterative Group Alignment

arXiv:2604.18966v1 Announce Type: cross Abstract: While language models have been adapted for tabular data generation, two fundamental limitations remain: (1) static fine-tuning produces models that c

local-aiarxiv-cs-ai

Sony AI says its autonomous ping pong robot is the first robot to attain expert-level performance in a physical sport after beating some top-level human players (Will Dunham/Reuters)

Will Dunham / Reuters: Sony AI says its autonomous ping pong robot is the first robot to attain expert-level performance in a physical sport after beating some top-level human players — An autonomous

agentstechmeme

Sparse Network Inference under Imperfect Detection and its Application to Ecological Networks

arXiv:2604.18820v1 Announce Type: cross Abstract: Recovering latent structure from count data has received considerable attention in network inference, particularly when one seeks both cross-group int

applicationsarxiv-cs-lg

Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation

arXiv:2601.02993v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a key paradigm for reducing factual hallucinations in Large Language Models (LLMs), yet little is kn

safetyarxiv-cs-cl

TEMPO: Scaling Test-time Training for Large Reasoning Models

arXiv:2604.19295v1 Announce Type: new Abstract: Test-time training (TTT) adapts model parameters on unlabeled test instances during inference time, which continuously extends capabilities beyond the r

The data heat island effect: quantifying the impact of AI data centers in a warming world

arXiv:2603.20897v3 Announce Type: replace-cross Abstract: The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable es

local-aiarxiv-cs-ai

Time Series Augmented Generation for Financial Applications

model-releasesarxiv-cs-ai

arXiv:2604.19633v1 Announce Type: new Abstract: Evaluating the reasoning capabilities of Large Language Models (LLMs) for complex, quantitative financial tasks is a critical and unsolved challenge. St

Towards a Linguistic Evaluation of Narratives: A Quantitative Stylistic Framework

arXiv:2604.19261v1 Announce Type: new Abstract: The evaluation of narrative quality remains a complex challenge, as it involves subjective factors such as plot, character development, and emotional im

researcharxiv-cs-cl

Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation

arXiv:2407.05102v2 Announce Type: replace-cross Abstract: Executing flow estimation using Deep Learning (DL)-based soft sensors on resource-limited IoT devices has demonstrated promise in terms of rel

local-aiarxiv-cs-ai

User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation

arXiv:2501.04410v2 Announce Type: replace Abstract: User simulation is an emerging interdisciplinary topic with multiple critical applications in the era of Generative AI. It involves creating an inte

Vibe coders are not going to like this. UC San Diego just published the first real field study of experienced developers using AI agents. Th…

Vibe coders are not going to like this. UC San Diego just published the first real field study of experienced developers using AI agents. They watched 13 of them code in the wild and surveyed 99 more.

agentsgary-marcus--x

Warmth and Competence in the Swarm: Designing Effective Human-Robot Teams

arXiv:2604.19270v1 Announce Type: new Abstract: As groups of robots increasingly collaborate with humans, understanding how humans perceive them is critical for designing effective human-robot teams.

agentsarxiv-cs-ro

WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent

arXiv:2604.17821v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have empowered autonomous web agents to execute natural language instructions directly on real-w

What’s new in GKE at Next ‘26

model-releasesgoogle-cloud-ai

This week at Google Cloud Next ‘26, we are sharing the evolution of Google Kubernetes Engine (GKE), delivering leading performance, efficiency, security, and scale for your most demanding and complex

When Can We Trust Deep Neural Networks? Towards Reliable Industrial Deployment with an Interpretability Guide

arXiv:2604.19206v1 Announce Type: new Abstract: The deployment of AI systems in safety-critical domains, such as industrial defect inspection, autonomous driving, and medical diagnosis, is severely ha

safetyarxiv-cs-cv

A Discordance-Aware Multimodal Framework with Multi-Agent Clinical Reasoning

arXiv:2604.16333v1 Announce Type: new Abstract: Knee osteoarthritis frequently exhibits discordance between structural damage observed in imaging and patient-reported symptoms such as pain. This misma

agentsarxiv-cs-lg

A Sensitivity Approach to Causal Inference Under Limited Overlap

arXiv:2511.22003v2 Announce Type: replace-cross Abstract: Limited overlap between treated and control groups is a key challenge in observational analysis. Standard approaches like trimming importance

A Text-To-Text Alignment Algorithm for Better Evaluation of Modern Speech Recognition Systems

arXiv:2509.24478v2 Announce Type: replace Abstract: Modern neural networks have greatly improved performance across speech recognition benchmarks. However, gains are often driven by frequent words wit

safetyarxiv-cs-cl

Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization

model-releasesarxiv-cs-cl

arXiv:2602.20743v2 Announce Type: replace Abstract: Anonymizing textual documents is a highly context-sensitive problem: the appropriate balance between privacy protection and utility preservation var

Tutorials

AI Data Transformation Guide for Data Engineers and Data Scientists

This guide from Databricks covers data transformation techniques and best practices essential for preparing data for AI/ML projects, addressing workflows that both data engineers and data scientists e

tutorialsdatabricks

AnchorSeg: Language Grounded Query Banks for Reasoning Segmentation

arXiv:2604.18562v1 Announce Type: new Abstract: Reasoning segmentation requires models to ground complex, implicit textual queries into precise pixel-level masks. Existing approaches rely on a single

local-aiarxiv-cs-cv