Search Results for author:
Found 12 papers, 4 papers with code
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
We propose the Chain-of-Table framework, where tabular data is explicitly used in the reasoning chain as a proxy for intermediate thoughts.
Ranked #3 on
Table-based Fact Verification
on TabFact
Transformers as Graph-to-Graph Models
We argue that Transformers are essentially graph-to-graph models, with sequences just being a special case.
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)
Text-to-SQL, the process of translating natural language into Structured Query Language (SQL), represents a transformative application of large language models (LLMs), potentially revolutionizing how humans interact with data.
Summarization with Precise Length Control
Many applications of text generation such as summarization benefit from accurately controlling the text length.
Document Summarization with Text Segmentation
In this paper, we exploit the innate document segment structure for improving the extractive summarization task.
Ranked #4 on
Text Summarization
on Arxiv HEP-TH citation graph
Attend to the Right Context: A Plug-and-Play Module for Content-Controllable Summarization
Content-Controllable Summarization generates summaries focused on the given controlling signals.
Graph Refinement for Coreference Resolution
The state-of-the-art models for coreference resolution are based on independent mention pair-wise decisions.
Ranked #8 on
Coreference Resolution
on OntoNotes
Neural Network based End-to-End Query by Example Spoken Term Detection
Here, we show that the CNN based matching outperforms DTW based matching using bottleneck features as well.
Selecting, Planning, and Rewriting: A Modular Approach for Data-to-Document Generation and Translation
In this paper, we report our system submissions to all 6 tracks of the WNGT 2019 shared task on Document-Level Generation and Translation.
Partially-supervised Mention Detection
Learning to detect entity mentions without using syntactic information can be useful for integration and joint optimization with other tasks.
Multilingual Bottleneck Features for Query by Example Spoken Term Detection
State of the art solutions to query by example spoken term detection (QbE-STD) usually rely on bottleneck feature representation of the query and audio document to perform dynamic time warping (DTW) based template matching.
Document-Level Neural Machine Translation with Hierarchical Attention Networks
Neural Machine Translation (NMT) can be improved by including document-level contextual information.
