Search: “research”

From Failure Taxonomy to Intervention: A Diagnostic Methodology for Industry-Scale AVLM in Video and Live-Streaming Platform Moderation

model-releasesarxiv-cs-lg

arXiv:2606.30059v1 Announce Type: new Abstract: Industry-scale video and live-streaming moderation imposes requirements that are difficult to satisfy with generic pretrained public models or external

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FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation

DGX agent

arXiv:2606.30367v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining sp

safetyarxiv-cs-ro

30 Jun 2026

GaRLILEO: Gravity-aligned Radar-Leg-Inertial Enhanced Odometry

arXiv:2511.13216v2 Announce Type: replace Abstract: Deployment of legged robots for navigating challenging terrains (e.g., stairs, slopes, and unstructured environments) has gained increasing preferen

applicationsarxiv-cs-ro

Generative Learning as a Tool to Improve Perception of Emotional Body Motion Expressions

arXiv:2606.28769v1 Announce Type: new Abstract: Emotional body motion expressions are an essential element of non-verbal communication. Effectively conveying these expressions through technology is of

safetyarxiv-cs-lg

GeoISF: Instance Semantic Forest Inspired Large-Scale Cross-View Geo-Localization via Ground LiDAR-to-Satellite Image

arXiv:2606.28371v1 Announce Type: new Abstract: The problem of localization on a large-scale satellite image given a frame of query ground view point clouds remains challenging. Existing LiDAR-to-imag

safetyarxiv-cs-cv

Grounding Sim-to-Real Generalization in Robotic Manipulation: An Empirical Study with Vision-Language-Action Models

arXiv:2603.22876v2 Announce Type: replace-cross Abstract: Learning a generalist control policy for robotic manipulation typically relies on large-scale datasets. Given the high cost of real-world data

How ChatGPT adoption has expanded

ChatGPT adoption has grown significantly since its launch, expanding across diverse user demographics, industries, and use cases globally. OpenAI's analysis likely covers metrics such as user growth,

model-releasesopenai

How Far Can You Get Without a GPU? A Systematic Benchmark of Lightweight Hallucination Detection Across Question Answering, Dialogue, and Summarisation

arXiv:2606.29809v1 Announce Type: cross Abstract: Hallucination detection has become a pressing requirement for trustworthy AI deployment at scale. The most accurate detection methods depend on GPU-in

How LLMs See Creativity: Zero-Shot Scoring of Visual Creativity with Interpretable Reasoning

arXiv:2606.29672v1 Announce Type: new Abstract: Evaluating the originality of visual images poses enduring challenges for creativity assessment. Automated scoring using AI models has proven effective

InsertAnywhere: Geometrically Grounded and Optics-Aware Video Object Insertion

arXiv:2512.17504v2 Announce Type: replace-cross Abstract: Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) rema

Inside Genebench-Pro

Genebench-Pro appears to be a case study or tool from OpenAI focused on benchmarking or evaluating genetic/genomic analysis capabilities, likely demonstrating how OpenAI's models or tools can be appli

model-releasesopenai

Is Muon as good as they say? We looked beyond training speed and found a hidden cost: Muon loses the simplicity bias of older optimizers lik…

Muon optimizer shows faster training speeds compared to traditional optimizers, but analysis reveals it sacrifices the simplicity bias that older optimizers maintain, potentially impacting model gener

safetyjeremy-howard--x

Learning from Reliable Latent Prompts for Visual Recognition with Missing Modalities

arXiv:2606.30597v1 Announce Type: new Abstract: Large-scale multimodal models (LMMs) have achieved superior performance in visual recognition by synergizing information across diverse, massive-scale p

Learning to Segment Liquids in Real-world Images

arXiv:2601.00940v2 Announce Type: replace Abstract: Liquids like water, wine and medicine are everywhere. However, limited attention has been given to the task of segmenting liquids, hindering the abi

Local Ai

Learning Where and When: Patch-Based Spatiotemporal Localization in Weakly Supervised Video Anomaly Detection

arXiv:2606.29498v1 Announce Type: new Abstract: Weakly supervised video anomaly detection (WSVAD) has predominantly focused on temporal localization, identifying when anomalies occur while largely neg

local-aiarxiv-cs-cv

LLM agents security duality: a comprehensive survey of self-security and empowered cybersecurity

arXiv:2606.28450v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly being integrated into real-world systems. Their autonomy and tool-use capabilities generate substantial

agentsarxiv-cs-ai

Local Ai

Low-cost concept-based localized explanations: How far can we get with training-free approaches?

arXiv:2606.29069v1 Announce Type: new Abstract: Concept-based Explainable AI (C-XAI) seeks human-understandable explanations grounded in semantic concepts, yet validation is limited by the scarcity of

local-aiarxiv-cs-ai

MaDI-Bench: An End-to-End Data Integration Benchmark

arXiv:2606.30371v1 Announce Type: cross Abstract: Data integration combines heterogeneous data sets into a single, coherent representation. Data integration involves a sequence of interdependent tasks

MAM-AI: An On-Device Medical Retrieval-Augmented Generation System for Nurses and Midwives in Zanzibar

arXiv:2606.29580v1 Announce Type: new Abstract: Maternal and newborn mortality remain among the highest in sub-Saharan Africa, where midwifery care is often delivered by nurses who lack midwifery trai

mamabench and mamaretrieval: Benchmarks for Evaluating Medical Retrieval-Augmented Generation in Maternal, Neonatal, and Reproductive Health

arXiv:2606.29467v1 Announce Type: new Abstract: Medical question-answering benchmarks rarely cover the maternal, neonatal, child, and reproductive-health questions a nurse-midwife asks, and, to our kn

MARS: A neurosymbolic approach for interpretable drug discovery

arXiv:2410.05289v4 Announce Type: replace Abstract: Background: Neurosymbolic (NeSy) artificial intelligence describes the combination of logic or rule-based techniques with neural networks. Compared

Memory has somehow consistently been the most exciting area of agent development over the last 3 years (imo), and it's still a largely unsol…

Memory has somehow consistently been the most exciting area of agent development over the last 3 years (imo), and it's still a largely unsolved problem!! Wiki's are the biggest advancement I've seen i

agentsharrison-chase--x

Memory-Managed Long-Context Attention: A Preliminary Study of Editable Request-Local Memory

arXiv:2606.28876v1 Announce Type: new Abstract: Long-context language models often conflate two different goals: compressing history into an efficient state, and maintaining reliable long-term memory.

MIRI Newsletter #126

Announcing: AI StopWatch In our last update, we mentioned we had something new in the works: a dedicated channel for news and analysis about AI. Subscribe to AI StopWatch An experiment from the writer

safetymiri

Modeling Earth-Scale Human-Like Societies with One Billion Agents

arXiv:2506.12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulat

agentsarxiv-cs-ai

MonoSR: Open-Vocabulary Spatial Reasoning from Monocular Images

arXiv:2511.19119v2 Announce Type: replace Abstract: Spatial reasoning (SR), the ability to infer 3D spatial information from 2D inputs, is essential for real-world applications such as embodied AI and

agentsarxiv-cs-cv

Multi-Class Human/Object Detection on Robot Manipulators using Proprioceptive Sensing

arXiv:2508.02425v2 Announce Type: replace-cross Abstract: In physical human-robot collaboration (pHRC) settings, humans and robots collaborate directly in shared environments. Robots must analyze inte

Multimodal Representation Alignment for Cross-modal Information Retrieval

arXiv:2506.08774v2 Announce Type: replace-cross Abstract: Different machine learning models can represent the same underlying concept in different ways. This variability is particularly valuable for i

Industry

New attack provides one more reason why AI browsers are a bad idea

AI browsers can be manipulated through prompt injection or memory poisoning to create false operational contexts where they bypass security guardrails, treating harmful actions as game logic rather th

industryars-technica

Not-quite-human tastes: the stylized omnivorousness of LLM survey surrogates

arXiv:2606.30085v1 Announce Type: new Abstract: Large-language models have proven to be remarkable if inconsistent parrots of public attitudes and opinions. The extent to which LLMs are able to produc

OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning

arXiv:2606.30378v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated promising spatial reasoning capabilities, while these abilities remain underexplored in the e

Local Ai

Online Data Selection for Instruction Tuning via Gaussian Processes

arXiv:2606.30077v1 Announce Type: cross Abstract: With Large Language Model (LLM) pre-training and fine-tuning shifting its focus from data volume to data quality, quality data selection has emerged a

local-aiarxiv-cs-ai

Industry

Our first summit dedicated to world models, coming to SF this September.

industrycristobal-valenzuela--x

Our first summit dedicated to world models, coming to SF this September. Announcing our first summit dedicated to world models, coming to SF this September. Very excited to have some incredible resear

Persona-Trained Monte Carlo: Estimating Market-Outcome Distributions via Swarms of Persona-Conditioned Neural Policy Bots in a Limit Order Book

arXiv:2606.29556v1 Announce Type: new Abstract: We propose Persona-Trained Monte Carlo (PTMC), a method for estimating distributions of market-outcome statistics by repeatedly simulating limit-order-b

safetyarxiv-cs-lg

Reinforcement Learning for Software Vulnerability Analysis: A Systematic Review with Emphasis on C/C++ Source Code and Static Analysis

arXiv:2606.28403v1 Announce Type: cross Abstract: Vulnerability detection in C/C++ software remains a major security challenge due to code complexity, manual memory management, and the limitations of

agentsarxiv-cs-ai

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation

arXiv:2606.28998v1 Announce Type: cross Abstract: Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM

Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation

arXiv:2602.09305v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate transformative potential, yet their reasoning remains inconsistent and unreliable. Reinforcement learning (

safetyarxiv-cs-lg

SA-Homo: Scale Adaptive Homography Estimation for Scale Variation Scenarios

arXiv:2606.30408v1 Announce Type: new Abstract: Homography estimation, as one of the fundamental problems in computer vision, remains challenged by scale variation scenarios where image pairs potentia

SADL: What to Ignore? A Benchmark for Subject-Aware Distractor Localization

arXiv:2606.30393v1 Announce Type: new Abstract: Photographs frequently contain visual distractors besides foregrounds and backgrounds of the intended subject, competing for attention and weakening com

ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration

ScarfBench is a benchmarking framework designed to evaluate AI agents' capabilities in migrating enterprise Java applications to modern frameworks. The benchmark likely assesses how well AI systems ca

applicationshugging-face

Solver-Verified Formulation Generation and Selection for Multi-Warehouse Inventory Allocation Using Large Language Models

arXiv:2606.29366v1 Announce Type: cross Abstract: Balance-oriented multi-warehouse inventory allocation is a recurring decision problem in large-scale e-commerce supply chains, in which a fixed replen

applicationsarxiv-cs-ai

StarDojo: Benchmarking Open-Ended Behaviors of Agentic Multimodal LLMs in Production-Living Simulations with Stardew Valley

arXiv:2507.07445v3 Announce Type: replace Abstract: Autonomous agents navigating human society must master both production activities and social interactions, yet existing benchmarks rarely evaluate t

Hardware

SwarmX: Agentic Scheduling for Low-Latency Agentic Systems

arXiv:2606.21401v2 Announce Type: replace-cross Abstract: Agentic AI applications compose multiple model calls and tool executions, creating new scheduling challenges for GPU-CPU clusters. Their infer

hardwarearxiv-cs-ai

SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?

arXiv:2511.06090v3 Announce Type: replace-cross Abstract: Optimizing the performance of large-scale software repositories demands expertise in code reasoning and software engineering (SWE) to reduce r

The entire business of the AI Labs & the potential speed of transformation stems from this fact.

applicationsethan-mollick--x

Ethan Mollick discusses a fundamental factor driving AI Labs' business model and the rapid pace of AI transformation. The post likely explores how a core principle or technological capability underpin

The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning

arXiv:2606.28843v1 Announce Type: cross Abstract: Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task. However, prior work has shown th

The Interference Gap: Comparing Retrieval Bounds in Human Memory and RAG Systems

arXiv:2606.28327v1 Announce Type: cross Abstract: How do retrieval bounds compare between human episodic memory and Retrieval-Augmented Generation (RAG) systems under semantic interference? We present

Industry

The US going 100% EV by 2040 would save more than 100k lives, study says

A study from the American Lung Association found that if the U.S. transitions to a 100% zero-emission passenger vehicle fleet by 2050, it would result in 89,300 fewer premature deaths and $978 billion

industryars-technica