@mipaltan Let’s embrace the change. !! @ImRo45 @hardikpandya7 @surya_14kumar @Jaspritbumrah93 #TATAIPL #AalaRe #MIvDC #DCvMI . 🧵 #Thread.

RT @Anuraag_Shukla: India's soils are silently starving. Over 70% lack nitrogen, 85% are low in organic carbon, and key micronutrients li….

Remarkable to see Llama 3.1 405B closing the gap with top closed-source models on MMLU. The rapid progress in open-weight models over the past 2 years is reshaping the field. While GPT-4 still leads, the democratization of cutting-edge NLP capabilities is accelerating.

Whose listening to this in 2024??.#WorldPeace #MiddleEastTensions .

🙌 To all #MumbaiIndians fans, let's embrace the changes and give our full support. Change is the only constant, and it brings new opportunities. Let's give a fair chance to new strategies and leadership for a stronger comeback! #BelieveInBlue @Jaspritbumrah93 @surya_14kumar.

🌟 #RohitSharma #IPL2023 Insights: Total Runs: 332, Highest Score: 65, Strike Rate: 132.37. Rohit's form sees an uptick with impactful innings.

🔥 #RohitSharma #IPL2022 Performance: Total Runs: 268, Highest Score: 48, Strike Rate: 120.18. A dip in form, but the captain's resilience never wavers.

📈 #RohitSharma #IPL2021 Highlights: Total Runs: 381, Highest Score: 63, Strike Rate: 127.42. A steady season for the Hitman. @ImRo45.

🤔 With the recent seasons' ups and downs, exploring new captaincy options makes sense from a management perspective. Fresh strategies could be the key to resurgence. #Leadership #IPL @ImRo45 @hardikpandya7.

🏆 #IPL2023 Insights: Despite a home win percentage of 71.42%, Mumbai Indians finished at the bottom. It's been a rollercoaster ride with highs and lows. #OneFamily #MumbaiIndians.

🔵 #IPL2022 Recap: A challenging season for Mumbai Indians, ending up last with a win percentage of 58.52%. The team showed spirit but will need to reflect and rebuild. Read more #MI #AalaRe.

🏏 #IPL2021 Update: Mumbai Indians showed resilience, finishing 5th with a win percentage of 56.7%. A tough fight but they missed the playoffs by a whisker. #MumbaiIndians #CricketFever @mipaltan.

Overall, the document highlights the challenges faced by LLMs in generating accurate texts and proposes CRAG as a method to address these challenges. Paper:

It shows the generalizability and adaptability of CRAG in enhancing the generation capabilities of LLMs.

4. Performance Improvement: Experimental results on various datasets demonstrate that CRAG significantly improves the performance of RAG-based approaches for both short- and long-form generation tasks.

This algorithm improves the utilization of retrieved data by refining the information extraction process.

3. Decompose-then-Recompose Algorithm: CRAG incorporates a decompose-then-recompose algorithm that selectively focuses on key information and filters out irrelevant information in the retrieved documents.

This helps to broaden the spectrum of retrieved information and complement the initially obtained documents.

2. Integration of Web Searches: To overcome the limitations of retrieval from static and limited corpora, large-scale web searches are integrated to augment the retrieval results.

It includes a lightweight retrieval evaluator to assess the quality of retrieved documents and trigger different retrieval actions based on confidence degrees.

1. Corrective Retrieval Augmented Generation (CRAG): CRAG is proposed as a method to improve the robustness of generation by self-correcting the results of retrieval and enhancing the utilization of retrieved documents.