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06/05/2023
Gen-IR @ SIGIR 2023: The First Workshop on Generative Information Retrieval
Generative information retrieval (IR) has experienced substantial growth...
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05/19/2023
How Does Generative Retrieval Scale to Millions of Passages?
Popularized by the Differentiable Search Index, the emerging paradigm of...
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12/19/2022
DSI++: Updating Transformer Memory with New Documents
Differentiable Search Indices (DSIs) encode a corpus of documents in the...
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12/16/2022
Dense Feature Memory Augmented Transformers for COVID-19 Vaccination Search Classification
With the devastating outbreak of COVID-19, vaccines are one of the cruci...
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10/20/2022
Transcending Scaling Laws with 0.1
Scaling language models improves performance but comes with significant ...
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07/21/2022
Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?
There have been a lot of interest in the scaling properties of Transform...
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05/02/2022
Retrieval-Enhanced Machine Learning
Although information access systems have long supported people in accomp...
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02/22/2022
A New Generation of Perspective API: Efficient Multilingual Character-level Transformers
On the world wide web, toxic content detectors are a crucial line of def...
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01/05/2022
Atomized Search Length: Beyond User Models
We argue that current IR metrics, modeled on optimizing user experience,...
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09/22/2021
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers
There remain many open questions pertaining to the scaling behaviour of ...
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07/14/2021
The Benchmark Lottery
The world of empirical machine learning (ML) strongly relies on benchmar...
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06/29/2021
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption
Self-supervised contrastive representation learning has proved incredibl...
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06/23/2021
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization
State-of-the-art models in natural language processing rely on separate ...
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05/12/2021
How Reliable are Model Diagnostics?
In the pursuit of a deeper understanding of a model's behaviour, there i...
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05/07/2021
Are Pre-trained Convolutions Better than Pre-trained Transformers?
In the era of pre-trained language models, Transformers are the de facto...
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05/05/2021
Rethinking Search: Making Experts out of Dilettantes
When experiencing an information need, users want to engage with an expe...
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03/01/2021
OmniNet: Omnidirectional Representations from Transformers
This paper proposes Omnidirectional Representations from Transformers (O...
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02/09/2021
Label Smoothed Embedding Hypothesis for Out-of-Distribution Detection
Detecting out-of-distribution (OOD) examples is critical in many applica...
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12/01/2020
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language Modeling
There are two major classes of natural language grammars – the dependenc...
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11/08/2020
Long Range Arena: A Benchmark for Efficient Transformers
Transformers do not scale very well to long sequence lengths largely bec...
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10/19/2020
Surprise: Result List Truncation via Extreme Value Theory
Work in information retrieval has largely been centered around ranking a...
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09/14/2020
Efficient Transformers: A Survey
Transformer model architectures have garnered immense interest lately du...
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08/17/2020
Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study
Large generative language models such as GPT-2 are well-known for their ...
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07/12/2020
HyperGrid: Efficient Multi-Task Transformers with Grid-wise Decomposable Hyper Projections
Achieving state-of-the-art performance on natural language understanding...
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05/02/2020
Synthesizer: Rethinking Self-Attention in Transformer Models
The dot product self-attention is known to be central and indispensable ...
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04/26/2020
Choppy: Cut Transformer For Ranked List Truncation
Work in information retrieval has traditionally focused on ranking and r...
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04/13/2020
Reverse Engineering Configurations of Neural Text Generation Models
This paper seeks to develop a deeper understanding of the fundamental pr...
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02/26/2020
Sparse Sinkhorn Attention
We propose Sparse Sinkhorn Attention, a new efficient and sparse method ...
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11/21/2019
Separate and Attend in Personal Email Search
In personal email search, user queries often impose different requiremen...
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06/19/2019
Domain Adaptation for Enterprise Email Search
In the enterprise email search setting, the same search engine often pow...
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09/15/2018