All entries

arXiv:2604.18627v1 Announce Type: new Abstract: Ensuring human safety is of paramount importance in warehouse environments that feature mixed traffic of human workers and autonomous mobile robots (AMR

arXiv:2510.27052v5 Announce Type: replace Abstract: Hallucination--defined here as generating statements unsupported or contradicted by available evidence or conversational context--remains a major ob

arXiv:2411.18275v2 Announce Type: replace Abstract: Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities. However, these models remain

arXiv:2509.16343v2 Announce Type: replace-cross Abstract: Building robust vision systems for high-stakes domains such as remote sensing requires stronger visual reasoning than what single-pass inferen

arXiv:2509.07966v2 Announce Type: replace-cross Abstract: Visual reasoning over structured data such as tables is a critical capability for modern vision-language models (VLMs), yet current benchmarks

arXiv:2604.19728v1 Announce Type: cross Abstract: We present VLA Foundry, an open-source framework that unifies LLM, VLM, and VLA training in a single codebase. Most open-source VLA efforts specialize

VLM Performance：Qwen3.6-27B is natively multimodal, supporting both vision-language thinking and non-thinking modes in a single unified checkpoint — the same as Qwen3.6-35B-A3B. It handles images and

arXiv:2604.19151v1 Announce Type: new Abstract: Existing Indic ASR benchmarks often use scripted, clean speech and leaderboard driven evaluation that encourages dataset specific overfitting. In additi

arXiv:2604.19609v1 Announce Type: new Abstract: Transformers have become a common foundation across deep learning, yet 3D scene understanding still relies on specialized backbones with strong domain p

arXiv:2507.21563v4 Announce Type: replace-cross Abstract: Recommendation systems often suffer from data sparsity caused by limited user-item interactions, which degrade their performance and amplify p

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.

Humans have been building ping-pong playing robots for decades, such as Omron's FOREPHUS that challenged amateur competitors at CES 2017. What sets Ace apart from the rest is that the robot, which was

arXiv:2508.00161v3 Announce Type: replace-cross Abstract: The releases of powerful open-weight large language models (LLMs) are often not accompanied by access to their full training data. Existing in

VideoGameBench is a new benchmark launched on Antim Labs, created by a1zhang, Thomas L. Griffiths, Karthik R. N, and Ofir Press. The benchmark likely evaluates AI model performance on video game-relat

We just hit #1 on the @huggingface BrowseComp-Plus leaderboard. Best accuracy: 92.53%. Best recall: 88.79%. Lowest calibration error across all submissions. Built with @AI21Labs Maestro. https://huggi

We need open traces so that everyone can train open agent models! cc @steipete @badlogicgames @thdxr @matanSF @hwchase17 People are misreading the SpaceX/Cursor deal as an M&A story. It’s actually a b

We want you to have a lot of AI! I don't know what they are doing over there, but Codex will continue to be available both in the FREE and PLUS ($20) plans. We have the compute and efficient models to

arXiv:2601.18891v3 Announce Type: replace Abstract: Caribou across the Arctic has declined in recent decades, motivating scalable and accurate monitoring approaches to guide evidence-based conservatio

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

By combining the analytical depth of Looker with Google’s Agentic Data Cloud, the potential to transform how we model, interact with, and act on our data appears limitless. This week at Google Cloud N

Google announced Ironwood, its seventh-generation TPU that is twice as power efficient as the previous generation, alongside specialized hardware designed to support the emerging agentic AI era. Ironw

We've published new research on how we post-train models for accurate search-augmented answers. Our SFT + RL pipeline improves search, citation quality, instruction following, and efficiency. With Qwe

What are the odds that the unnamed senator who called the effort to pass the SAVE America Act a “charade” professes unqualified support for the bill when talking to constituents and donors? Statistica

arXiv:2604.19440v1 Announce Type: new Abstract: Recent work has demonstrated the promise of orchestrating large language models (LLMs) within evolutionary and agentic optimization systems. However, th

Replit enables dramatically accelerated software development cycles, reducing deployment timelines from 9 months to 3 days through its cloud-based development platform. The platform streamlines the bu

What's cooler than finding a 27-year-old bug in OpenBSD? Finding a positive cosmological constant hiding for over a century in the algebra of relativity🌌 No new physics or math needed🧮 Possibly the mo

Succeeding in the agentic era requires a transformation in your data strategy: moving from human-scale to agent-first workloads, evolving from reactive intelligence to proactive action, and shifting f

From vibe-coded and large-scale apps to AI models and agents, Cloud Run delivers on-demand compute with zero overhead and pay-per-use pricing for all of your workloads. Last year, the number of extern

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

Companies are shifting from gen AI that simply answers questions to autonomous agents that perceive, reason, and act on their behalf. Attempting to scale these agents on legacy stacks exposes structur

At Google Cloud Next, we’re announcing a range of compute capabilities to enable your core general purpose and AI workloads for the agentic world with higher performance and lower costs. Why it matter

While generative AI sparked a revolution, the true paradigm shift is the rapid evolution from standalone AI models to multi-agent autonomous systems. In this new era, the network transcends basic conn

AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem

arXiv:2604.19335v1 Announce Type: new Abstract: The rapid growth of chemical literature has generated vast amounts of unstructured data, where reaction information is particularly valuable for applica

arXiv:2602.11199v2 Announce Type: replace Abstract: Large language models (LLMs) often respond even when prompts omit critical details or include misleading information, leading to hallucinations or r

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

arXiv:2512.02304v2 Announce Type: replace Abstract: Large language models (LLMs) can act as both problem solvers and solution verifiers, where the latter select high-quality answers from a pool of sol

arXiv:2604.19514v1 Announce Type: cross Abstract: The consensus that GCN, GraphSAGE, GAT, and EvolveGCN outperform feature-only baselines on the Elliptic Bitcoin Dataset is widely cited but has not be

arXiv:2509.25630v2 Announce Type: replace-cross Abstract: Efficient sampling from complex and high dimensional target distributions turns out to be a fundamental task in diverse disciplines such as sc

arXiv:2604.19001v1 Announce Type: new Abstract: Large reasoning models (LRMs) produce complex, multi-step reasoning traces, yet safety evaluation remains focused on final outputs, overlooking how harm

arXiv:2604.18880v1 Announce Type: cross Abstract: LLMs frequently generate fictitious yet convincing citations, often expressing high confidence even when the underlying reference is wrong. We study t

... which keeps things confusing, since it raises an important new question https://x.com/simonw/status/2046798283700617267 @TheAmolAvasare If I sign up for a new $20/month account today and roll the

arXiv:2402.06922v5 Announce Type: replace-cross Abstract: Large language model (LLM)-based agents combine LLMs with external tools to automate tasks such as scheduling meetings, managing documents, or

arXiv:2409.18660v2 Announce Type: replace-cross Abstract: Feedback from artificial intelligence (AI) is increasingly easy to access and research has already established that people learn from it. But

arXiv:2604.18586v1 Announce Type: cross Abstract: Vaccination remains a cornerstone of global public health, yet the COVID-19 pandemic exposed how online misinformation, political polarization, and de

arXiv:2603.24472v2 Announce Type: replace Abstract: Self-distillation has emerged as an effective post-training paradigm for LLMs, often improving performance while shortening reasoning traces. Howeve