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Omar Khattab on neural information retrieval
アーカイブされたシリーズ ("無効なフィード" status)
When? This feed was archived on February 26, 2024 22:33 (). Last successful fetch was on March 01, 2023 02:11 ()
Why? 無効なフィード status. サーバーは持続期間に有効なポッドキャストのフィードを取得することができませんでした。
What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.
Manage episode 329207362 series 3352614
Pronouncing "ColBERT", the origins of ColBERT, doing NLP from an IR perspective, how getting "scooped" can be productive, OpenQA and related tasks, PhD journeys, why even retrieval plus attention is not all you need, multilingual knowledge-intensive NLP, and aiming high in research projects.
Transcript: https://web.stanford.edu/class/cs224u/podcast/khattab/
- Omar's website
- Matei Zaharia
- Keshav Santhanam
- Steven Colbert thowing paper with Obama
- The ColBERT paper and the ColBERTv2 paper
- DeepImpact: Learning passage impacts for inverted indexes
- DPR: Dense passage retrieval for open-domain question answering
- Incorporating query term independence assumption for efficient retrieval and ranking using deep neural networks
- DeepCT: Context-aware sentence/passage term importance estimation for first stage retrieval
- Reading Wikipedia to answer open-domain questions
- ORQA: Latent retrieval for weakly supervised open domain question answering
- QRECC
- ColBERT-QA: Relevance-guided Supervision for OpenQA with ColBERT
- Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval
- Passage reranking with BERT
- UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering
- Self-driving search engines: The neural hype and comparisons against weak baselines
- Mohammad Hammoud
- RAG: Retrieval-augmented generation for knowledge-intensive NLP tasks
- Hindsight: Posterior-guided training of retrievers for improved open-ended generation
- Learning Cross-Lingual IR from an English Retriever
- Blog post: A moderate proposal for radically better AI-powered Web search
- Blog post: Building scalable, explainable, and adaptive NLP models with retrieval
- XOR-TyDi
16 つのエピソード
アーカイブされたシリーズ ("無効なフィード" status)
When? This feed was archived on February 26, 2024 22:33 (). Last successful fetch was on March 01, 2023 02:11 ()
Why? 無効なフィード status. サーバーは持続期間に有効なポッドキャストのフィードを取得することができませんでした。
What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.
Manage episode 329207362 series 3352614
Pronouncing "ColBERT", the origins of ColBERT, doing NLP from an IR perspective, how getting "scooped" can be productive, OpenQA and related tasks, PhD journeys, why even retrieval plus attention is not all you need, multilingual knowledge-intensive NLP, and aiming high in research projects.
Transcript: https://web.stanford.edu/class/cs224u/podcast/khattab/
- Omar's website
- Matei Zaharia
- Keshav Santhanam
- Steven Colbert thowing paper with Obama
- The ColBERT paper and the ColBERTv2 paper
- DeepImpact: Learning passage impacts for inverted indexes
- DPR: Dense passage retrieval for open-domain question answering
- Incorporating query term independence assumption for efficient retrieval and ranking using deep neural networks
- DeepCT: Context-aware sentence/passage term importance estimation for first stage retrieval
- Reading Wikipedia to answer open-domain questions
- ORQA: Latent retrieval for weakly supervised open domain question answering
- QRECC
- ColBERT-QA: Relevance-guided Supervision for OpenQA with ColBERT
- Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval
- Passage reranking with BERT
- UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering
- Self-driving search engines: The neural hype and comparisons against weak baselines
- Mohammad Hammoud
- RAG: Retrieval-augmented generation for knowledge-intensive NLP tasks
- Hindsight: Posterior-guided training of retrievers for improved open-ended generation
- Learning Cross-Lingual IR from an English Retriever
- Blog post: A moderate proposal for radically better AI-powered Web search
- Blog post: Building scalable, explainable, and adaptive NLP models with retrieval
- XOR-TyDi
16 つのエピソード
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