Pavan Kapanipathi
@pavankaps
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408
Following
674
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Statuses
818
Researcher at IBM Research (Views are my own)
White Plains, NY
Joined May 2009
RT @arankomatsuzaki: Putting It All into Context: Simplifying Agents with LCLMs. Putting all the core code in the context often leads to be….
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We, at IBM, released a new dataset for evaluating nested API sequencing and its on huggingface now.
NESTFUL: A benchmark for nested API calls from @IBMResearch . - 1.8K+ executable function sequences.- Tests math reasoning & coding tools.- Evaluates variable handling & chaining.- Shows gaps in current LLM capabilities. Apache 2.0 licensed & fully reproducible
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RT @krvarshney: Look at those beautiful Granite Guardian safety vests! #brand #bootleg. The Granite Guardian technical report is now on arX….
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RT @harsha_kokel: 🚨 New Dataset Alert🚨 . We introduce ACP Bench. A question-answering style dataset that evaluates AI-model's ability to re….
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RT @prasatti: We released best-in-class Apache 2.0 licensed models for detecting general harm and RAG hallucinations as part of the Granite….
huggingface.co
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RT @aviaviavi__: Announcing "@IBM SWE-Agent 1.0", from my team @IBMResearch , the first SWE-Agent built only on top of open-source models w….
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RT @neurobongo: 🎉Today, we're pleased to announce the release of the Granite 3.0 model family, the latest open-licensed, general purpose LL….
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RT @Yikang_Shen: Granite 3.0 is our latest update for the IBM foundation models. The 8B and 2B models outperform strong competitors with si….
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RT @seirasto: Are you building and evaluating RAG systems? Presenting InspectorRAGet a platform for easily analyzin….
arxiv.org
Large Language Models (LLM) have become a popular approach for implementing Retrieval Augmented Generation (RAG) systems, and a significant amount of effort has been spent on building good models...
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RT @_akhaliq: IBM presents API-BLEND. A Comprehensive Corpora for Training and Benchmarking API LLMs. There is a growing need for Large Lan….
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RT @jerryjliu0: Self-RAG in @llama_index. We’re excited to feature Self-RAG, a special RAG technique where an LLM can do self-reflection fo….
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RT @RamonAstudill12: We are releasing `v0.5.4` version of the transition-amr-parser. Now with document-level AMR parsing, instalable from P….
github.com
SoTA Abstract Meaning Representation (AMR) parsing with word-node alignments in Pytorch. Includes checkpoints and other tools such as statistical significance Smatch. - IBM/transition-amr-parser
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RT @dariogila: We can all agree we’re at a unique and evolutionary moment in AI, with enterprises increasingly turning to this technology’s….
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RT @aviaviavi__: If you're using GPT-3 or any other LLMs read this:.1. Don't want it to hallucinate?.2. Need attribution for generated answ….
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RT @ylecun: Good article on LLMs at Forbes. The media are starting to agree with my much-criticized statements about LLMs. "LLMs as they….
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RT @payel791: Happy to see that our chemical language foundation model, MoLFormer is highlighted in @NatComputSci. In addition to showing c….
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RT @asimunawar: Join us today for a very exciting 3rd day of IBM Neuro-Symbolic AI Workshop 2023. Day 3 is all about NLP, large language mo….
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RT @luislamb: @IBMResearch workshop on Neurosymbolic AI on the way. Alex Gray opening and @vardi on Deep Learning and Deep Reasoning - Neur….
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RT @krvarshney: .@ArvindKrishna summarizes our efforts at @IBM and @IBMResearch on responsible and trustworthy AI in this video. This is pr….
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