Models1 min read
AI for Societal Impact
Explore this collection to see how experts and local leaders are using AI breakthroughs to ensure everyone can share the opportunity of AI.
From Google AI blog
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Models1 min read
Explore this collection to see how experts and local leaders are using AI breakthroughs to ensure everyone can share the opportunity of AI.
From Google AI blog
Models1 min read
Animation of several words in different languages slowly zooming past
From Google AI blog
Photo: Yan Krukau
Text "AI & Economy Atlas v1.0 2026" with the Google G and a spinning globe illustration
From Google AI blog
AI1 min read
Salesforce Koa is built on Nvidia's open-weight Nemotron model and is trained to do sales, marketing, and customer-support tasks.
From TechCrunch AI
Research1 min read
arXiv:2609.13457v1 Announce Type: new Abstract: Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for question-answering tasks. However, these...
From arXiv cs.AI
LLMs1 min read
arXiv:2609.13481v1 Announce Type: new Abstract: Large language models have made abstractive summarization remarkably fluent, but generated summaries can hallucinate facts, posing serious risks in biomedical and clinical domains. We addre...
From arXiv cs.CL
LLMs1 min read
arXiv:2609.13151v1 Announce Type: new Abstract: Leading multilingual speech recognition models like Whisper transcribe diverse, low-resource languages without language-specific training but are computationally expensive to deploy. Token ...
From arXiv cs.CL
LLMs1 min read
arXiv:2609.13158v1 Announce Type: new Abstract: Large Vision--Language Models (LVLMs) are increasingly expected to perform visual question answering (VQA) over planar media. However, existing planar VQA benchmarks typically emphasize iso...
From arXiv cs.CL
Research1 min read
arXiv:2609.13470v1 Announce Type: new Abstract: Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challenges for deployment in agentic pipeline...
From arXiv cs.AI
LLMs1 min read
arXiv:2609.13238v1 Announce Type: new Abstract: Maxillofacial report generation from cone beam computed tomography is scored here by a composite objective placing 80% of its weight on a large language model judgement of factual entailmen...
From arXiv cs.CL
Research1 min read
arXiv:2609.13491v1 Announce Type: new Abstract: The strong performance of AI Agents across an impressive variety of tasks is driving an unprecedented investment in agentic infrastructures, however the cost of processing tokens is fast in...
From arXiv cs.AI
Research1 min read
arXiv:2609.13356v1 Announce Type: new Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: comp...
From arXiv cs.AI
LLMs1 min read
arXiv:2609.13445v1 Announce Type: new Abstract: Speech-to-speech LLMs like Moshi, and its derivative PersonaPlex, can listen and speak concurrently through full-duplex generation. However, they can begin speaking inappropriately during p...
From arXiv cs.CL
Research1 min read
arXiv:2609.13436v1 Announce Type: new Abstract: Large Language Model (LLM) agents offer a promising path toward autonomously managing long-term physical tasks without human intervention. However, physical tasks require agents to continuo...
From arXiv cs.AI
LLMs1 min read
arXiv:2609.13520v1 Announce Type: new Abstract: While Large Language Models have improved rapidly, many fundamental questions remain about how to evaluate the knowledge and reasoning abilities they acquire, and how such evaluations relat...
From arXiv cs.CL
Research1 min read
arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding how and when that occurs is essentia...
From arXiv cs.AI
LLMs1 min read
arXiv:2609.13685v1 Announce Type: new Abstract: Negation remains a longstanding challenge for both language models (LMs) and large language models (LLMs). Prior work mainly focuses on a small set of high-frequency single-word negation cu...
From arXiv cs.CL
LLMs1 min read
arXiv:2609.13709v1 Announce Type: new Abstract: Human corrections identify editable spans, but the examples receiving corrections may come from a selective feedback channel. We analyze this interaction at a fixed model checkpoint by deco...
From arXiv cs.CL
LLMs1 min read
arXiv:2609.13556v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown remarkable proficiency on general-purpose tasks, yet their performance often degrades in highly-specialized technical domains. Moreover, little is kn...
From arXiv cs.CL
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