Jimin Sun
@jimin__sun
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RT @SoYeonTiffMin: 🚨🚨 Preprint Alert 🚨🚨 🚀🚀.As AI become agents 🤖, how can we reliably delegate tasks to them, if they cannot communicate t….
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RT @cohere: Today, we’re launching early access for North!. Our all-in-one secure AI workspace platform combines LLMs, search, and agents i….
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RT @cohere: Introducing Command R7B: the smallest, fastest, and final model in our R series of enterprise-focused LLMs!. It delivers a powe….
cohere.com
The smallest model in our R series delivers top-tier speed, efficiency, and quality to build powerful AI applications on commodity GPUs and edge devices.
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RT @SoYeonTiffMin: I am on the industry job market, and am planning to interview around next March. I am attending @NeurIPSConf, and I hope….
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RT @cohere: Introducing our latest AI search model: Rerank 3.5!. Rerank 3.5 delivers state-of-the-art performance with improved reasoning a….
cohere.com
Rerank 3.5 delivers improved reasoning and multilingual capabilities to search complex enterprise data with greater accuracy.
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RT @lltjuatja: 💬 Have you or a loved one compared LM probabilities to human linguistic acceptability judgments? You may be overcompensating….
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Just landed in Miami to attend #EMNLP2024 🐊 . I’ll be presenting the poster of our “Tools fail” paper on Wednesday Nov 13th, 16:00-17:30 at Jasmine — come check out our poster for a chat!.
Tools augment LLMs but can also introduce errors without explicit messages. Can LLMs detect these "silent" tool-based errors?. We investigate this challenge and present an initial approach to failure recovery. Work w/ @SoYeonTiffMin @_Yingshan @ybisk. 🗞️
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RT @sarahookr: Extremely proud to share ✨ Aya Expanse ✨. We are a small lab, and this builds on years of dedicated research to connect the….
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RT @viddivj: 🧵1/8 So annoying when my 🤖 vacuum cleaner buzzes loudly during my Zoom meeting! Can we teach robots to be aware of their noise….
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RT @aidangomez: Today @CohereForAI and @cohere are releasing two new multilingual models spanning 23 popular languages. Across a range of u….
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RT @aidangomez: Your search can see now. We're excited to release fully multimodal embeddings for folks to start building with! https://t.….
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RT @nlpxuhui: 1/ What if you could see how your AI handles the chaos of the real world? Meet HAICOSYSTEM: the framework to simulate human-A….
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RT @SNAT02792153: Synthetic data can boost LLM’s reasoning—how?. Introducing MIND—a method to boost LLM’s math reasoning by generating dial….
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RT @jerelev: 🤖💡 Brainstorming with ChatGPT’s help?. ⚠️ Be careful what you reveal about yourself, because large language models might give….
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Excited to share that my recent paper “Tools Fail: Detecting Silent Errors in Faulty Tools” got accepted to @emnlpmeeting ! See you in Miami 🌴🐊.
Tools augment LLMs but can also introduce errors without explicit messages. Can LLMs detect these "silent" tool-based errors?. We investigate this challenge and present an initial approach to failure recovery. Work w/ @SoYeonTiffMin @_Yingshan @ybisk. 🗞️
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RT @SoYeonTiffMin: In recent years, we have seen progress of foundation models (RT-X models and V/LLM's) as embodied agents. However, metho….
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RT @TEKnologyy: 🚀 Excited to announce our latest paper, "Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation"….
arxiv.org
Despite the central role of retrieval in retrieval-augmented generation (RAG) systems, much of the existing research on RAG overlooks the well-established field of fair ranking and fails to...
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RT @TEKnologyy: (1/9) 🧠 Ever wondered if there's a unified framework for RAG? We've formalized the retrieval enhancement paradigm with cons….
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