@librarian-bot\n\t recommend

\n","updatedAt":"2024-02-15T10:51:30.288Z","author":{"_id":"60107b385ac3e86b3ea4fc34","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1627505688463-60107b385ac3e86b3ea4fc34.jpeg","fullname":"Daniel van Strien","name":"davanstrien","type":"user","isPro":true,"isHf":true,"isHfAdmin":false,"isMod":false,"followerCount":705}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.7918877601623535},"editors":["davanstrien"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/1627505688463-60107b385ac3e86b3ea4fc34.jpeg"],"reactions":[],"isReport":false}},{"id":"65cdecb6a6aa872fce9237ab","author":{"_id":"63d3e0e8ff1384ce6c5dd17d","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1674830754237-63d3e0e8ff1384ce6c5dd17d.jpeg","fullname":"Librarian Bot (Bot)","name":"librarian-bot","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":264},"createdAt":"2024-02-15T10:51:34.000Z","type":"comment","data":{"edited":false,"hidden":false,"latest":{"raw":"This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [MAPLE: Multilingual Evaluation of Parameter Efficient Finetuning of Large Language Models](https://huggingface.co/papers/2401.07598) (2024)\n* [Enhancing Amharic-LLaMA: Integrating Task Specific and Generative Datasets](https://huggingface.co/papers/2402.08015) (2024)\n* [RomanSetu: Efficiently unlocking multilingual capabilities of Large Language Models models via Romanization](https://huggingface.co/papers/2401.14280) (2024)\n* [Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning](https://huggingface.co/papers/2402.04833) (2024)\n* [H2O-Danube-1.8B Technical Report](https://huggingface.co/papers/2401.16818) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`","html":"

This is an automated message from the Librarian Bot. I found the following papers similar to this paper.

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The following papers were recommended by the Semantic Scholar API

\n

\n
• MAPLE: Multilingual Evaluation of Parameter Efficient Finetuning of Large Language Models (2024)
\n
• Enhancing Amharic-LLaMA: Integrating Task Specific and Generative Datasets (2024)
\n
• RomanSetu: Efficiently unlocking multilingual capabilities of Large Language Models models via Romanization (2024)
\n
• Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning (2024)
\n
• H2O-Danube-1.8B Technical Report (2024)
\n

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Please give a thumbs up to this comment if you found it helpful!

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If you want recommendations for any Paper on Hugging Face checkout this Space

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You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: \n\n@librarian-bot\n\t recommend

\n","updatedAt":"2024-02-15T10:51:34.280Z","author":{"_id":"63d3e0e8ff1384ce6c5dd17d","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1674830754237-63d3e0e8ff1384ce6c5dd17d.jpeg","fullname":"Librarian Bot (Bot)","name":"librarian-bot","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":264}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.718184769153595},"editors":["librarian-bot"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/1674830754237-63d3e0e8ff1384ce6c5dd17d.jpeg"],"reactions":[],"isReport":false}},{"id":"67dd0a43067589b43b2d661b","author":{"_id":"659b890eb0f43ed69fef0955","avatarUrl":"/avatars/244e977b5dcbed18d4827e480a4b1bac.svg","fullname":"BhagyashreeWagh","name":"BhagyashreeWagh","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false},"createdAt":"2025-03-21T06:42:11.000Z","type":"comment","data":{"edited":true,"hidden":true,"hiddenBy":"","hiddenReason":"Off-Topic","latest":{"raw":"This comment has been hidden","html":"This comment has been hidden","updatedAt":"2025-03-21T06:43:58.741Z","author":{"_id":"659b890eb0f43ed69fef0955","avatarUrl":"/avatars/244e977b5dcbed18d4827e480a4b1bac.svg","fullname":"BhagyashreeWagh","name":"BhagyashreeWagh","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false}},"numEdits":0,"editors":[],"editorAvatarUrls":[],"reactions":[]}}],"primaryEmailConfirmed":false,"paper":{"id":"2401.15006","authors":[{"_id":"65bdd0a5358734fd09cbf04b","name":"Jay Gala","hidden":false},{"_id":"65bdd0a5358734fd09cbf04c","name":"Thanmay Jayakumar","hidden":false},{"_id":"65bdd0a5358734fd09cbf04d","name":"Jaavid Aktar Husain","hidden":false},{"_id":"65bdd0a5358734fd09cbf04e","name":"Aswanth Kumar M","hidden":false},{"_id":"65bdd0a5358734fd09cbf04f","user":{"_id":"63ef3cd11e695b35aa48bebc","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/BnOgZiv1IHKbtTaFTWpAZ.png","isPro":false,"fullname":"Mohammed Safi Ur Rahman Khan","user":"safikhan","type":"user"},"name":"Mohammed Safi Ur Rahman Khan","status":"claimed_verified","statusLastChangedAt":"2024-10-18T12:15:35.176Z","hidden":false},{"_id":"65bdd0a5358734fd09cbf050","name":"Diptesh Kanojia","hidden":false},{"_id":"65bdd0a5358734fd09cbf051","name":"Ratish Puduppully","hidden":false},{"_id":"65bdd0a5358734fd09cbf052","name":"Mitesh M. Khapra","hidden":false},{"_id":"65bdd0a5358734fd09cbf053","name":"Raj Dabre","hidden":false},{"_id":"65bdd0a5358734fd09cbf054","name":"Rudra Murthy","hidden":false},{"_id":"65bdd0a5358734fd09cbf055","name":"Anoop Kunchukuttan","hidden":false}],"publishedAt":"2024-01-26T17:07:08.000Z","title":"Airavata: Introducing Hindi Instruction-tuned LLM","summary":"We announce the initial release of \"Airavata,\" an instruction-tuned LLM for\nHindi. Airavata was created by fine-tuning OpenHathi with diverse,\ninstruction-tuning Hindi datasets to make it better suited for assistive tasks.\nAlong with the model, we also share the IndicInstruct dataset, which is a\ncollection of diverse instruction-tuning datasets to enable further research\nfor Indic LLMs. Additionally, we present evaluation benchmarks and a framework\nfor assessing LLM performance across tasks in Hindi. Currently, Airavata\nsupports Hindi, but we plan to expand this to all 22 scheduled Indic languages.\nYou can access all artifacts at https://ai4bharat.github.io/airavata.","upvotes":4,"discussionId":"65bdd0a6358734fd09cbf088","ai_summary":"Airavata, an instruction-tuned LLM for Hindi, was developed using diverse datasets and includes evaluation benchmarks and a performance assessment framework.","ai_keywords":["instruction-tuned LLM","OpenHathi","IndicInstruct dataset","evaluation benchmarks","Indic languages"]},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"60107b385ac3e86b3ea4fc34","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1627505688463-60107b385ac3e86b3ea4fc34.jpeg","isPro":true,"fullname":"Daniel van Strien","user":"davanstrien","type":"user"},{"_id":"62a3bb1cd0d8c2c2169f0b88","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62a3bb1cd0d8c2c2169f0b88/eT2TS0IlQbZtz-F_zHLz9.jpeg","isPro":false,"fullname":"Joseph [open/acc] Pollack","user":"Tonic","type":"user"},{"_id":"6538119803519fddb4a17e10","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/6538119803519fddb4a17e10/ffJMkdx-rM7VvLTCM6ri_.jpeg","isPro":false,"fullname":"samusenps","user":"samusenps","type":"user"},{"_id":"66496b507ab33d141d90597c","avatarUrl":"/avatars/7d8b467fab00b40bd7148ef6a2643425.svg","isPro":false,"fullname":"Varun T","user":"thevarun","type":"user"}],"acceptLanguages":["*"]}">