ResFields: Residual Neural Fields for Spatiotemporal Signals
🖥 Github: https://github.com/markomih/ResFields
📕 Paper: https://arxiv.org/pdf/2309.03160.pdf
🔥 Dataset: https://paperswithcode.com/dataset/nerf
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/markomih/ResFields
📕 Paper: https://arxiv.org/pdf/2309.03160.pdf
🔥 Dataset: https://paperswithcode.com/dataset/nerf
https://news.1rj.ru/str/DataScienceT
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🚩 Towards the TopMost: A Topic Modeling System Toolkit
The highly cohesive and decoupled modular design of TopMost enables quick utilization, fair comparisons, and flexible extensions of different topic models.
🖥 Github: https://github.com/bobxwu/topmost
📕 Paper: https://arxiv.org/abs/2309.06908v1
⏩ Docs: https://topmost.readthedocs.io/
⭐️ Dataset: https://paperswithcode.com/dataset/imdb-movie-reviews
https://news.1rj.ru/str/DataScienceT
The highly cohesive and decoupled modular design of TopMost enables quick utilization, fair comparisons, and flexible extensions of different topic models.
$ pip install topmost🖥 Github: https://github.com/bobxwu/topmost
📕 Paper: https://arxiv.org/abs/2309.06908v1
⏩ Docs: https://topmost.readthedocs.io/
⭐️ Dataset: https://paperswithcode.com/dataset/imdb-movie-reviews
https://news.1rj.ru/str/DataScienceT
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📂 An Open-source Framework for Autonomous Language Agents
Agents is carefully engineered to support important features including planning, memory, tool usage, multi-agent communication, and fine-grained symbolic control.
🖥 Github: https://github.com/aiwaves-cn/agents
📕 Paper: https://arxiv.org/pdf/2309.07870.pdf
⏩ Demo: https://github.com/aiwaves-cn/agents#web-demos
⭐️ Project: http://www.aiwaves-agents.com/
https://news.1rj.ru/str/DataScienceT
Agents is carefully engineered to support important features including planning, memory, tool usage, multi-agent communication, and fine-grained symbolic control.
pip install ai-agents🖥 Github: https://github.com/aiwaves-cn/agents
📕 Paper: https://arxiv.org/pdf/2309.07870.pdf
⏩ Demo: https://github.com/aiwaves-cn/agents#web-demos
⭐️ Project: http://www.aiwaves-agents.com/
https://news.1rj.ru/str/DataScienceT
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LightTBNet
🖥 Github: https://github.com/dani-capellan/LightTBNet
📕 Paper: https://arxiv.org/pdf/2309.02140v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/montgomery-county-x-ray-set
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/dani-capellan/LightTBNet
📕 Paper: https://arxiv.org/pdf/2309.02140v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/montgomery-county-x-ray-set
https://news.1rj.ru/str/DataScienceT
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Forwarded from Data Science Library
We have just launched a fundraising campaign for the channel to ensure continued quality service
We upload the book via Internet data, and this is expensive for us
Participate and contribute to the donation campaign until the target amount is reached
Members who will contribute to the donation campaign will receive a free subnoscription to the paid channel and a LinkedIn grant
Donate link:
https://boosty.to/datascienceteam/donate
We upload the book via Internet data, and this is expensive for us
Participate and contribute to the donation campaign until the target amount is reached
Members who will contribute to the donation campaign will receive a free subnoscription to the paid channel and a LinkedIn grant
Donate link:
https://boosty.to/datascienceteam/donate
👍3
💥 MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
MMICL is a multimodal vision-language model with the ability to analyze and understand multiple images, as well as follow instructions.
🖥 Github: https://github.com/haozhezhao/mic
📕 Paper: https://arxiv.org/abs/2309.07915v1
⭐️ Datasets: https://paperswithcode.com/dataset/mmbench
https://news.1rj.ru/str/DataScienceT
MMICL is a multimodal vision-language model with the ability to analyze and understand multiple images, as well as follow instructions.
🖥 Github: https://github.com/haozhezhao/mic
📕 Paper: https://arxiv.org/abs/2309.07915v1
⭐️ Datasets: https://paperswithcode.com/dataset/mmbench
https://news.1rj.ru/str/DataScienceT
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LLM_Fine_Tuning_Molecular_Properties
🖥 Github: https://github.com/SylwiaNowakowska/LLM_Fine_Tuning_Molecular_Properties
📕 Paper: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/65030b55b338ec988a780108/original/chem-ber-ta-2-fine-tuning-for-molecule-s-hiv-replication-inhibition-prediction.pdf
🔥 Dataset: https://paperswithcode.com/dataset/moleculenet
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/SylwiaNowakowska/LLM_Fine_Tuning_Molecular_Properties
📕 Paper: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/65030b55b338ec988a780108/original/chem-ber-ta-2-fine-tuning-for-molecule-s-hiv-replication-inhibition-prediction.pdf
🔥 Dataset: https://paperswithcode.com/dataset/moleculenet
https://news.1rj.ru/str/DataScienceT
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🦙 LLaVA: Large Language and Vision Assistant
🖥 Github: https://github.com/haotian-liu/LLaVA
📕 Paper: https://arxiv.org/pdf/2309.09958v1.pdf
⭐️ Datasets: https://paperswithcode.com/dataset/mmlu
https://news.1rj.ru/str/DataScienceT
git clone https://github.com/haotian-liu/LLaVA.git
cd LLaVA🖥 Github: https://github.com/haotian-liu/LLaVA
📕 Paper: https://arxiv.org/pdf/2309.09958v1.pdf
⭐️ Datasets: https://paperswithcode.com/dataset/mmlu
https://news.1rj.ru/str/DataScienceT
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LLMKE
🖥 Github: https://github.com/bohuizhang/llmke
📕 Paper: https://arxiv.org/pdf/2309.08491v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/lama
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/bohuizhang/llmke
📕 Paper: https://arxiv.org/pdf/2309.08491v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/lama
https://news.1rj.ru/str/DataScienceT
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⛓️🛠️ ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing
🖥 Github: https://github.com/ianarawjo/ChainForge
⭐️ Project: https://chainforge.ai
📕 Paper: https://arxiv.org/abs/2309.09128v1
https://news.1rj.ru/str/DataScienceT
pip install chainforge🖥 Github: https://github.com/ianarawjo/ChainForge
⭐️ Project: https://chainforge.ai
📕 Paper: https://arxiv.org/abs/2309.09128v1
https://news.1rj.ru/str/DataScienceT
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😠 GPTFUZZER : Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
Fuzzer maintains over 90% attack success rate against ChatGPT and Llama-2 models.
🖥 Github: https://github.com/sherdencooper/gptfuzz
📕 Paper: https://arxiv.org/abs/2309.10253v1
⏩ Dataset: https://sites.google.com/view/llm-jailbreak-study
https://news.1rj.ru/str/DataScienceT
Fuzzer maintains over 90% attack success rate against ChatGPT and Llama-2 models.
🖥 Github: https://github.com/sherdencooper/gptfuzz
📕 Paper: https://arxiv.org/abs/2309.10253v1
⏩ Dataset: https://sites.google.com/view/llm-jailbreak-study
https://news.1rj.ru/str/DataScienceT
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Distillation-in-dg
🖥 Github: https://github.com/vorobeevich/distillation-in-dg
📕 Paper: https://arxiv.org/pdf/2309.11446v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/office-home
https://news.1rj.ru/str/DataScienceT
🖥 Github: https://github.com/vorobeevich/distillation-in-dg
📕 Paper: https://arxiv.org/pdf/2309.11446v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/office-home
https://news.1rj.ru/str/DataScienceT
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