vishwajeet kumar @vishwajeet_86
Research Scientist at IBM Research AI | Interested in Natural Language Processing and Machine Learning | IIT Bombay Joined June 2010-
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Github 👨🔧: Awesome-GraphRAG A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation. github .com/DEEP-PolyU/Awesome-GraphRAG
I implemented GRPO and DPO from scratch in vanilla Pytorch to unravel every piece of training details. Hope it could be helpful for those who care about the implementation details of the algorithms. 👉 github.com/mingyin0312/RL… #AI #RL #LLM
Announcing the ICLR 2026 Call for Papers! Abstract submission: Sept 19 (AoE) Paper submission: Sept 24 (AoE) Reviews released: Nov 11 Author/Reviewer discussion: Nov 11-Dec 3 Final decisions: Jan 22 2026 iclr.cc/Conferences/20…
ColBERT and ColPali are amazing. But they're also bankrupting your infrastructure budget. Remember when multi-vector embeddings meant choosing between quality and your AWS bill? 𝗠𝗨𝗩𝗘𝗥𝗔 (Multi-Vector Retrieval via Fixed Dimensional Encodings) 𝗵𝗮𝘀 𝗺𝗮𝗱𝗲 𝗶𝗻𝘀𝗮𝗻𝗲…
Our open models are here. Both of them. openai.com/open-models
Claude Code Templates There is no time-wasting in this community. This Claude Code template collection looks really cool. You probably need to customize them further, but it's a good place to find inspiration.
NVIDIA just dropped paper exposing a $57 billion AI industry mistake. While Big Tech keeps pushing expensive LLMs like ChatGPT & Claude... Small language models handle 70% of AI agent work at 1/30th the cost. Here's why this changes everything: (hint: less is more)
The paper argues the next big thing is the Agentic Web where autonomous AI agents, not humans, run tasks across the internet. The authors show how the Web has already shifted from early pages to mobile feeds and now toward agent‑driven action. They define 3 dimensions,…
Wow. This is a HUGE 24-trillion-token web dataset with document-level metadata available on @huggingface apache-2.0 license - collected from Common Crawl - each document is labeled with a 12-field taxonomy covering topic, page type, complexity, and quality . - Labels are…
Beautiful @GoogleResearch paper. LLMs can learn in context from examples in the prompt, can pick up new patterns while answering, yet their stored weights never change. That behavior looks impossible if learning always means gradient descent. The mechanisms through which this…
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A 24-trillion-token web dataset with document-level metadata just dropped on @huggingface License: apache-2.0 ESSENTIAL-WEB v1.0 collects 24 trillion tokens from Common Crawl. Each document is labeled with a 12-field taxonomy covering topic, page type, complexity, and quality…
I am pleased to announce a new version of my RL tutorial. Major update to the LLM chapter (eg DPO, GRPO, thinking), minor updates to the MARL and MBRL chapters and various sections (eg offline RL, DPG, etc). Enjoy! arxiv.org/abs/2412.05265
Our paper, Dictionaries to the Rescue: Cross-Lingual Vocabulary Transfer for Low-Resource Languages Using Bilingual Dictionaries, has been accepted to #ACL2025NLP Findings! Thanks to the co-authors, @Yusuke196 , Justin, @yusuke1997 , @alanyttian , @h_kamiga , @tarowatanabe !
Super thrilled to share GMMLU is accepted to #ACL2025 main conference 🎉 It was also recently recognised by @StanfordHAI as one of the significant AI releases of 2024 🚀 I had a blast collaborating on this closely with @beyzaermis and all our collaborators! Huge congrats!💙
Super thrilled to share GMMLU is accepted to #ACL2025 main conference 🎉 It was also recently recognised by @StanfordHAI as one of the significant AI releases of 2024 🚀 I had a blast collaborating on this closely with @beyzaermis and all our collaborators! Huge congrats!💙
📢 A reminder that the NeurIPS deadline for full paper submission is May 15th (Anywhere on Earth, AOE). We look forward to receiving your work, good luck to all submitting authors!
Want to 𝐜𝐮𝐭 𝐑𝐅𝐓 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐭𝐢𝐦𝐞 𝐛𝐲 𝐮𝐩 𝐭𝐨 𝟐× and boost performance? 🚀 Meet 𝑨𝒅𝒂𝑹𝑭𝑻 — a lightweight, plug-and-play curriculum learning method you can drop into any mainstream RFT algorithms (PPO, GRPO, REINFORCE). Less compute. Better results. 🧵 1/n
Universal RAG RAG is dead, they said. Then you see papers like this and it gives you a better understanding of the opportunities and challenges ahead. Lots of great ideas in this paper. I've summarized a few below:

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