Stéphane Clinchant (@sclincha) profile picture
Joined November 2014
Photo by Stéphane Clinchant (@sclincha)Photo by Stéphane Clinchant (@sclincha)
Stéphane Clinchant retweeted
Introducing SPARSEUP: the first model release from @Linkup_platform , and the missing sparse companion of DenseOn and LateOn. Same backbone, same data, <150M, 56+ on BEIR-13. The model is open-source, use it! Blog: linkup.so/blog/introducing-s… Model: huggingface.co/Linkup-Platfo… (Apache 2.0)
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Stéphane Clinchant retweeted
Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search Naver introduces a sparse retriever that directly indexes visual documents and serves text queries without neural query encoding. 📝 arxiv.org/abs/2605.30917 👨🏽‍💻 github.com/naver/v-splade
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Stéphane Clinchant retweeted
I told you it would be a stacked line-up! @N1colAIs @thibault_formal and @antoine_chaffin talking tomorrow at the Search Meetup™️ (along with others whose twitter @ I don't have) Join us for nice presentations and chats ❤️
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Stéphane Clinchant retweeted
Databricks is proud to be a Founding Gold Sponsor of @TheOfficialACM Conference on AI and Agentic Systems—the first ACM conference dedicated to compound AI and agentic systems, with our co-founder @matei_zaharia on the organizing committee. Join us May 26–29 in San Jose for the premier event for rigorous, reproducible research in compound AI architectures, optimization, and deployment. Register today: caisconf.org/
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Stéphane Clinchant retweeted
Most code search systems rely on dense embeddings. In this work, we release SPLADE-Code, learned sparse retrieval models for code retrieval, with strong generalization, high interpretability, compatibility with inverted indexes, and working across 20+ programming languages.
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Stéphane Clinchant retweeted
New sparse retrieval model: introducing SPLARE, which extends SPLADE by replacing the vocabulary head with pretrained SAEs! paper: arxiv.org/abs/2603.13277 (ICLR'26) also how we won the WSDM'26 Cup on multilingual retrieval: arxiv.org/abs/2602.20986 (model weights coming soon!)
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Stéphane Clinchant retweeted
𝘏𝘶𝘮𝘢𝘯𝘴 𝘵𝘩𝘪𝘯𝘬 𝘧𝘭𝘶𝘪𝘥𝘭𝘺—𝘯𝘢𝘷𝘪𝘨𝘢𝘵𝘪𝘯𝘨 𝘢𝘣𝘴𝘵𝘳𝘢𝘤𝘵 𝘤𝘰𝘯𝘤𝘦𝘱𝘵𝘴 𝘦𝘧𝘧𝘰𝘳𝘵𝘭𝘦𝘴𝘴𝘭𝘺, 𝘧𝘳𝘦𝘦 𝘧𝘳𝘰𝘮 𝘳𝘪𝘨𝘪𝘥 𝘭𝘪𝘯𝘨𝘶𝘪𝘴𝘵𝘪𝘤 𝘣𝘰𝘶𝘯𝘥𝘢𝘳𝘪𝘦𝘴. But current reasoning models remain constrained by discrete tokens, limiting their full potential. Introducing 𝐒𝐨𝐟𝐭 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠: a training-free method that mimics human-like “soft” reasoning by generating continuous, abstract concept tokens. These tokens smoothly blend multiple meanings through probability-weighted mixtures of embeddings, enabling richer representations and seamless exploration of diverse reasoning paths. 𝐓𝐡𝐞 𝐢𝐦𝐩𝐚𝐜𝐭? ✅ Improved accuracy on math & code benchmarks by up to 2.48% (pass@1). ✅ Reduced token usage by up to 22.4%, making reasoning models both smarter and more efficient.
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Stéphane Clinchant retweeted
Arrived in Singapore for #ICLR2025 and will be presenting PROVENCE on Friday, Poster session 3 at 10am, poster #255! Blogpost: huggingface.co/blog/nadiinch… Will be happy to meet & chat about #LLMs, #RAG, #InformationRetrieval and #MultilingualNLP :) #NLProc @naverlabseurope
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Stéphane Clinchant retweeted
AllenAI COOKED, Llama 3.1 Tulu 405B beats DeepSeek V3 - all whilst being 40% SMALLER! 🔥 Fully open model weights, data and training pipeline 🤗
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Stéphane Clinchant retweeted
What a great pleasure and honor to share this session about generative AI, ethics, bias, and politics with 3 passionate speakers @plimantour, Andrew Wyckoff, and Juha Heikkilä. Thanks @AI2S2Symposium for the invitation. See you in Geneva on Monday!
⭐️ We're thrilled to unveil the complete lineup of keynote speakers at #AI2S2 in Geneva, Switzerland next week! 🗣️ Get ready for a knowledge-packed experience. Check out the full agenda here: ai2s2.org/2023/event ❗️ Act fast – free registration ends tonight!
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Stéphane Clinchant retweeted
I will present our #ACL paper “Should you marginalize over possible tokenizations?” on Wednesday, Jul 12, 11:00-12:30, at Poster session 7! Come to chat about tokenization in LMs. w/ @germank @josrzn @MarcDymetman. arxiv.org/abs/2306.17757
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Stéphane Clinchant retweeted
Outstanding!
If you happen to be in Toronto for ACL, you might want to disco on July 10 at 11am virtual2023.aclweb.org/paper…
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Stéphane Clinchant retweeted
Excited to share our #ACL2023 paper "Memory-efficient NLLB-200: Language-specific Expert Pruning of a Massively Multilingual Machine Translation Model". arxiv:arxiv.org/abs/2212.09811 Joint work w/ Alexandre Berard, Vassilina Nikoulina during my internship @naverlabseurope 1/6
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Stéphane Clinchant retweeted
📢 REMINDER for TREC-AToMiC participants! News: Test topics are out! 🎉 Check them here: trec-atomic.github.io/annouc…. We've carefully selected 200 sections from vital Wikipedia articles. Get ready for some fascinating exploration! Happy searching! 🚀
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Stéphane Clinchant retweeted
Before signing off for the weekend sign up for next week's 📢 Open virtual seminar w @alireza_mshi Ph.D.@EPFL and @idiap_ch-@uzh_en ! Reference-Free Metric for Evaluating Question Generation by Answering the Question 📅Tue 16th May 9.30am CEST Register: tinyurl.com/uxzvaddr
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Stéphane Clinchant retweeted
📢 Introducing MPT: a new family of open-source commercially usable LLMs from @MosaicML. Trained on 1T tokens of text+code, MPT models match and - in many ways - surpass LLaMa-7B. This release includes 4 models: MPT-Base, Instruct, Chat, & StoryWriter (🧵) mosaicml.com/blog/mpt-7b
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Stéphane Clinchant retweeted
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved With Text 103M documents containing 585M images interleaved with 43B English tokens github.com/allenai/mmc4
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Stéphane Clinchant retweeted
Sequence length 65k, anyone?
Updated @MosaicML LLM training throughput tables. Here are some highlights: - Best HFU: 73.63%!!! 🚀 13B w/ act ckpt - Best MFU: 62.09%!!! 🔥 3B w/out act ckpt - Train with SeqLen 65k 🤯 Details here: github.com/mosaicml/examples… [1/5]
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Stéphane Clinchant retweeted
Want to build your own chat AI from scratch? We're launching a Building LLMs course at @Data_AI_Summit to teach everyone how to build a Dolly clone: databricks.com/dataaisummit. Tiny model, big attitude, for anyone. #DemocratizeAI
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