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data/2409.11074.json

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+{"paper_url": "https://huggingface.co/papers/2409.11074", "comment": "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* [Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process](https://huggingface.co/papers/2407.20311) (2024)\n* [Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems](https://huggingface.co/papers/2408.16293) (2024)\n* [Benchmarking Chinese Knowledge Rectification in Large Language Models](https://huggingface.co/papers/2409.05806) (2024)\n* [RedWhale: An Adapted Korean LLM Through Efficient Continual Pretraining](https://huggingface.co/papers/2408.11294) (2024)\n* [AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs](https://huggingface.co/papers/2409.11404) (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`"}

data/2409.11363.json

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+{"paper_url": "https://huggingface.co/papers/2409.11363", "comment": "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* [SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories](https://huggingface.co/papers/2409.07440) (2024)\n* [OpenDevin: An Open Platform for AI Software Developers as Generalist Agents](https://huggingface.co/papers/2407.16741) (2024)\n* [PyBench: Evaluating LLM Agent on various real-world coding tasks](https://huggingface.co/papers/2407.16732) (2024)\n* [Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents](https://huggingface.co/papers/2408.07060) (2024)\n* [AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?](https://huggingface.co/papers/2407.15711) (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`"}

data/2409.11901.json

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+{"paper_url": "https://huggingface.co/papers/2409.11901", "comment": "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* [PERSOMA: PERsonalized SOft ProMpt Adapter Architecture for Personalized Language Prompting](https://huggingface.co/papers/2408.00960) (2024)\n* [Comparing Retrieval-Augmentation and Parameter-Efficient Fine-Tuning for Privacy-Preserving Personalization of Large Language Models](https://huggingface.co/papers/2409.09510) (2024)\n* [Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation](https://huggingface.co/papers/2408.03533) (2024)\n* [Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation](https://huggingface.co/papers/2408.09698) (2024)\n* [PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization](https://huggingface.co/papers/2407.18078) (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`"}

data/2409.12106.json

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+{"paper_url": "https://huggingface.co/papers/2409.12106", "comment": "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* [Language Models Show Stable Value Orientations Across Diverse Role-Plays](https://huggingface.co/papers/2408.09049) (2024)\n* [Assessing Generative Language Models in Classification Tasks: Performance and Self-Evaluation Capabilities in the Environmental and Climate Change Domain](https://huggingface.co/papers/2408.17362) (2024)\n* [Personality Alignment of Large Language Models](https://huggingface.co/papers/2408.11779) (2024)\n* [WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback](https://huggingface.co/papers/2408.15549) (2024)\n* [Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form Text](https://huggingface.co/papers/2408.09235) (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`"}

data/2409.12134.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2409.12134", "comment": "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* [Scaling Up Summarization: Leveraging Large Language Models for Long Text Extractive Summarization](https://huggingface.co/papers/2408.15801) (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`"}

data/2409.12183.json

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+{"paper_url": "https://huggingface.co/papers/2409.12183", "comment": "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* [Strategic Chain-of-Thought: Guiding Accurate Reasoning in LLMs through Strategy Elicitation](https://huggingface.co/papers/2409.03271) (2024)\n* [Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models](https://huggingface.co/papers/2408.02442) (2024)\n* [DiPT: Enhancing LLM reasoning through diversified perspective-taking](https://huggingface.co/papers/2409.06241) (2024)\n* [Language Models Benefit from Preparation with Elicited Knowledge](https://huggingface.co/papers/2409.01345) (2024)\n* [Fine-tuning Smaller Language Models for Question Answering over Financial Documents](https://huggingface.co/papers/2408.12337) (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`"}

data/2409.12186.json

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+{"paper_url": "https://huggingface.co/papers/2409.12186", "comment": "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* [To Code, or Not To Code? Exploring Impact of Code in Pre-training](https://huggingface.co/papers/2408.10914) (2024)\n* [XMainframe: A Large Language Model for Mainframe Modernization](https://huggingface.co/papers/2408.04660) (2024)\n* [OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection](https://huggingface.co/papers/2407.16237) (2024)\n* [CodeACT: Code Adaptive Compute-efficient Tuning Framework for Code LLMs](https://huggingface.co/papers/2408.02193) (2024)\n* [DOMAINEVAL: An Auto-Constructed Benchmark for Multi-Domain Code Generation](https://huggingface.co/papers/2408.13204) (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`"}

data/2409.12191.json

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+{"paper_url": "https://huggingface.co/papers/2409.12191", "comment": "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* [TC-LLaVA: Rethinking the Transfer from Image to Video Understanding with Temporal Considerations](https://huggingface.co/papers/2409.03206) (2024)\n* [VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation](https://huggingface.co/papers/2409.04429) (2024)\n* [Shaking Up VLMs: Comparing Transformers and Structured State Space Models for Vision&Language Modeling](https://huggingface.co/papers/2409.05395) (2024)\n* [mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models](https://huggingface.co/papers/2408.04840) (2024)\n* [LLaVA-SG: Leveraging Scene Graphs as Visual Semantic Expression in Vision-Language Models](https://huggingface.co/papers/2408.16224) (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`"}