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AI@Stanford AND Arxiv Doc

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23 Documents

[2404.03592] ReFT: Representation Finetuning for Language Models

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2024-04-08 About

[2401.18059] RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

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2024-02-03 About

[2304.09848] Evaluating Verifiability in Generative Search Engines

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2023-04-23 About

[2304.01982] Rethinking the Role of Token Retrieval in Multi-Vector Retrieval

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2023-04-05 About

[2203.14465] STaR: Bootstrapping Reasoning With Reasoning

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2023-02-07 About

[2301.04709] Causal Abstraction for Faithful Model Interpretation

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2023-01-14 About

[2212.01340] Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking

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2022-12-06 About

[2210.09338] Deep Bidirectional Language-Knowledge Graph Pretraining

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2022-10-23 About

[2208.01066] What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

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2022-09-17 About

[2204.08173] TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval

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2022-05-11 About

[2204.08491] Active Learning Helps Pretrained Models Learn the Intended Task

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2022-04-20 About

[2203.13088] Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction

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2022-03-30 About

[2006.05987] Revisiting Few-sample BERT Fine-tuning

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2022-03-21 About

[2004.12832] ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

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2022-01-12 About

[2007.00814] Relevance-guided Supervision for OpenQA with ColBERT

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2022-01-07 About

[2112.01488] ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

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2021-12-05 About

[2104.12016] Learning Passage Impacts for Inverted Indexes

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2021-10-08 About

[2010.00402] From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering

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2020-10-03 About

[2007.04612] Concept Bottleneck Models

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2020-07-10 About

[2007.00077] Similarity Search for Efficient Active Learning and Search of Rare Concepts

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2020-07-02 About

[2006.09462] Selective Question Answering under Domain Shift

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2020-06-30 About

[1911.00172] Generalization through Memorization: Nearest Neighbor Language Models

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2019-12-20 About

[1807.00082] Amanuensis: The Programmer's Apprentice

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**The use of natural language to facilitate communication
between the expert programmer and apprentice AI system.**

> an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon **insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems** that leverage and extend the state of the art in machine learning **by integrating human and machine intelligence**. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants.

> [#Dehaene](/tag/stanislas_dehaene)'s work extends the [#Global Workspace Theory](/tag/global_workspace_theory) of Bernard Baars. Dehaene’s version of the theory combined with Yoshua Bengio’s concept of a [#consciousness prior](/tag/consciousness_prior.html) and deep reinforcement learning suggest a model for constructing and maintaining the cognitive states that arise and persist during complex problem solving.

2019-11-12 About