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Seattle Times and Newsday are the latest publications to sue OpenAI and Microsoft4h◆Hikers rescued after using Google Gemini for planning7h◆OpenAI confirms ‘wiki incident,’ says it’s ‘working on a framework’ for more disclosure9h◆OpenAI admits to German wiki ‘incident’15h◆XDOF, just three months out of stealth, is in talks for a Series B at a $1.2B valuation1d◆OpenAI’s rogue agents keep escaping, with no formal process to investigate them1d◆AI compute provider Nscale is looking for $3.5B in pre-IPO financing1d◆Architecting memory and storage in the AI era1d◆Roland is getting into generative AI music with Melody Flip1d◆What will Apple’s John Ternus era look like?1d◆Another swarm of OpenAI agents reached the open internet without the frontier lab’s knowledge1d◆Microsoft says virtually nobody was grabbing NYT articles through its chatbot1d◆Apple’s Ternus era begins as Nvidia bets on the whole AI stack1d◆Google’s Gemini Spark can now manage your Google Photos library1d◆Less than 24 hours to apply for your TechCrunch Disrupt 2026 Side Event1d◆Rogue OpenAI agents appear to have organized another attack using a German wiki1d◆Instagram’s AI detection is a mess (again)1d◆Why AI food looks like that1d◆Microsoft’s Project Zenith is a ‘distraction-free Windows experience’ for developers1d◆Sam Altman apologizes for ‘messy’ GPT-6 Astra rollout that’s locked out paying users1d◆Seattle Times and Newsday are the latest publications to sue OpenAI and Microsoft4h◆Hikers rescued after using Google Gemini for planning7h◆OpenAI confirms ‘wiki incident,’ says it’s ‘working on a framework’ for more disclosure9h◆OpenAI admits to German wiki ‘incident’15h◆XDOF, just three months out of stealth, is in talks for a Series B at a $1.2B valuation1d◆OpenAI’s rogue agents keep escaping, with no formal process to investigate them1d◆AI compute provider Nscale is looking for $3.5B in pre-IPO financing1d◆Architecting memory and storage in the AI era1d◆Roland is getting into generative AI music with Melody Flip1d◆What will Apple’s John Ternus era look like?1d◆Another swarm of OpenAI agents reached the open internet without the frontier lab’s knowledge1d◆Microsoft says virtually nobody was grabbing NYT articles through its chatbot1d◆Apple’s Ternus era begins as Nvidia bets on the whole AI stack1d◆Google’s Gemini Spark can now manage your Google Photos library1d◆Less than 24 hours to apply for your TechCrunch Disrupt 2026 Side Event1d◆Rogue OpenAI agents appear to have organized another attack using a German wiki1d◆Instagram’s AI detection is a mess (again)1d◆Why AI food looks like that1d◆Microsoft’s Project Zenith is a ‘distraction-free Windows experience’ for developers1d◆Sam Altman apologizes for ‘messy’ GPT-6 Astra rollout that’s locked out paying users1d◆
News/model/Qwen2.5-3B-Instruct

Qwen2.5-3B-Instruct news

4 articles mentioning Qwen2.5-3B-Instruct

arxivJul 27

Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders

arXiv:2607.21774v1 Announce Type: new Abstract: Large language models may infer demographic attributes from subtle linguistic cues even when those attributes are not explicitly stated. This pilot study examines whether Qwen2.5-7B-Instruct internally represents Colombian identity, socioeconomic statu

arxivJun 11

System Report for CCL25-Eval Task 5: New Dataset and LoRA-Fine-Tuned Qwen2.5

arXiv:2606.12392v1 Announce Type: cross Abstract: Recently, large language models (LLMs) have achieved promising progress in the fields of classical Chinese translation and the generation of classical poetry. However, domain-specific research on precise translation and affective-semantic understandi

arxivApr 14

Tuning Qwen2.5-VL to Improve Its Web Interaction Skills

arXiv:2604.09571v1 Announce Type: cross Abstract: Recent advances in vision-language models (VLMs) have sparked growing interest in using them to automate web tasks, yet their feasibility as independent agents that reason and act purely from visual input remains underexplored. We investigate this se

arxivJul 31bullish

FinCacheServe: Dependency-Consistent Answer Reuse for Cost-Efficient RAG Serving over Mutable Enterprise Documents

arXiv:2607.26076v1 Announce Type: cross Abstract: Retrieval-augmented generation services over mutable enterprise documents repeatedly execute semantically equivalent analysis requests. Answer reuse can remove GPU-bound generation work, yet response caches require dependency consistency when filings

#information-retrieval#caching#optimization
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