Search Results for author: Jeffrey Dalton

Found 20 papers, 7 papers with code

Open Assistant Toolkit -- version 2

1 code implementation1 Mar 2024 Sophie Fischer, Federico Rossetto, Carlos Gemmell, Andrew Ramsay, Iain Mackie, Philip Zubel, Niklas Tecklenburg, Jeffrey Dalton

We present the second version of the Open Assistant Toolkit (OAT-v2), an open-source task-oriented conversational system for composing generative neural models.

Code Generation Response Generation +1

Controllable Chest X-Ray Report Generation from Longitudinal Representations

no code implementations9 Oct 2023 Francesco Dalla Serra, Chaoyang Wang, Fani Deligianni, Jeffrey Dalton, Alison Q O'Neil

Previous approaches to automated radiology reporting generally do not provide the prior study as input, precluding comparison which is required for clinical accuracy in some types of scans, and offer only unreliable methods of interpretability.

Anatomy Representation Learning +1

Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting

no code implementations30 Aug 2023 Francesco Dalla Serra, Chaoyang Wang, Fani Deligianni, Jeffrey Dalton, Alison Q. O'Neil

Automated approaches to radiology reporting require the image to be encoded into a suitable token representation for input to the language model.

Image Captioning Language Modelling

Adaptive Latent Entity Expansion for Document Retrieval

no code implementations29 Jun 2023 Iain Mackie, Shubham Chatterjee, Sean MacAvaney, Jeffrey Dalton

First, we demonstrate that applying a strong neural re-ranker before sparse or dense PRF can improve the retrieval effectiveness by 5-8%.

Re-Ranking Retrieval

GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval

no code implementations16 Jun 2023 Iain Mackie, Ivan Sekulic, Shubham Chatterjee, Jeffrey Dalton, Fabio Crestani

Recent studies show that Generative Relevance Feedback (GRF), using text generated by Large Language Models (LLMs), can enhance the effectiveness of query expansion.

Document Ranking Retrieval

Generative and Pseudo-Relevant Feedback for Sparse, Dense and Learned Sparse Retrieval

no code implementations12 May 2023 Iain Mackie, Shubham Chatterjee, Jeffrey Dalton

Pseudo-relevance feedback (PRF) is a classical approach to address lexical mismatch by enriching the query using first-pass retrieval.

Document Ranking Retrieval

Generative Relevance Feedback with Large Language Models

no code implementations25 Apr 2023 Iain Mackie, Shubham Chatterjee, Jeffrey Dalton

Current query expansion models use pseudo-relevance feedback to improve first-pass retrieval effectiveness; however, this fails when the initial results are not relevant.

Language Modelling Retrieval

Generate, Transform, Answer: Question Specific Tool Synthesis for Tabular Data

no code implementations17 Mar 2023 Carlos Gemmell, Jeffrey Dalton

Tabular question answering (TQA) presents a challenging setting for neural systems by requiring joint reasoning of natural language with large amounts of semi-structured data.

Question Answering

DocuT5: Seq2seq SQL Generation with Table Documentation

no code implementations11 Nov 2022 Elena Soare, Iain Mackie, Jeffrey Dalton

We perform experiments on the Spider family of datasets that contain complex questions that are cross-domain and multi-table.

Domain Generalization Language Modelling +1

Query-Specific Knowledge Graphs for Complex Finance Topics

no code implementations8 Nov 2022 Iain Mackie, Jeffrey Dalton

This workshop paper discusses automating the construction of query-specific document and entity knowledge graphs (KGs) for complex research topics.

Document Ranking Knowledge Graphs +1

GRILLBot: An Assistant for Real-World Tasks with Neural Semantic Parsing and Graph-Based Representations

no code implementations31 Aug 2022 Carlos Gemmell, Iain Mackie, Paul Owoicho, Federico Rossetto, Sophie Fischer, Jeffrey Dalton

GRILLBot is the winning system in the 2022 Alexa Prize TaskBot Challenge, moving towards the next generation of multimodal task assistants.

Semantic Parsing

Induced Natural Language Rationales and Interleaved Markup Tokens Enable Extrapolation in Large Language Models

1 code implementation24 Aug 2022 Mirelle Bueno, Carlos Gemmell, Jeffrey Dalton, Roberto Lotufo, Rodrigo Nogueira

Our experimental results show that generating step-by-step rationales and introducing marker tokens are both required for effective extrapolation.

Language Modelling

VILT: Video Instructions Linking for Complex Tasks

2 code implementations23 Aug 2022 Sophie Fischer, Carlos Gemmell, Iain Mackie, Jeffrey Dalton

This work addresses challenges in developing conversational assistants that support rich multimodal video interactions to accomplish real-world tasks interactively.


CODEC: Complex Document and Entity Collection

2 code implementations9 May 2022 Iain Mackie, Paul Owoicho, Carlos Gemmell, Sophie Fischer, Sean MacAvaney, Jeffrey Dalton

We also show that the manual query reformulations significantly improve document ranking and entity ranking performance.

Document Ranking Re-Ranking +1

Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions

1 code implementation EMNLP 2021 Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin, Jeffrey Dalton, Mikhail Burtsev

Enabling open-domain dialogue systems to ask clarifying questions when appropriate is an important direction for improving the quality of the system response.

CEQE: Contextualized Embeddings for Query Expansion

no code implementations9 Mar 2021 Shahrzad Naseri, Jeffrey Dalton, Andrew Yates, James Allan

We find that CEQE outperforms static embedding-based expansion methods on multiple collections (by up to 18% on Robust and 31% on Deep Learning on average precision) and also improves over proven probabilistic pseudo-relevance feedback (PRF) models.

Re-Ranking Retrieval

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