Search Results for author:
Found 21 papers, 10 papers with code
DocFinQA: A Long-Context Financial Reasoning Dataset
For large language models (LLMs) to be effective in the financial domain -- where each decision can have a significant impact -- it is necessary to investigate realistic tasks and data.
BizBench: A Quantitative Reasoning Benchmark for Business and Finance
We demonstrate that the current bottleneck in performance is due to LLMs' limited business and financial understanding, highlighting the value of a challenging benchmark for quantitative reasoning within this domain.
Learning Answer Generation using Supervision from Automatic Question Answering Evaluators
Recent studies show that sentence-level extractive QA, i. e., based on Answer Sentence Selection (AS2), is outperformed by Generation-based QA (GenQA) models, which generate answers using the top-k answer sentences ranked by AS2 models (a la retrieval-augmented generation style).
Knowledge Transfer from Answer Ranking to Answer Generation
In this paper, we propose to train a GenQA model by transferring knowledge from a trained AS2 model, to overcome the aforementioned issue.
Cross-Lingual Open-Domain Question Answering with Answer Sentence Generation
Our cross-lingual generative system outperforms answer sentence selection baselines for all 5 languages and monolingual generative pipelines for three out of five languages studied.
Extracting and Inferring Personal Attributes from Dialogue
Personal attributes represent structured information about a person, such as their hobbies, pets, family, likes and dislikes.
Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text
To support the broad range of real machine errors that can be identified by laypeople, the ten error categories of Scarecrow -- such as redundancy, commonsense errors, and incoherence -- are identified through several rounds of crowd annotation experiments without a predefined ontology.
Go Forth and Prosper: Language Modeling with Ancient Textual History
This method can improve perplexity of pretrained LMs with no updates to the LM's own parameters.
Extracting Summary Knowledge Graphs from Long Documents
Knowledge graphs capture entities and relations from long documents and can facilitate reasoning in many downstream applications.
A Controllable Model of Grounded Response Generation
Current end-to-end neural conversation models inherently lack the flexibility to impose semantic control in the response generation process, often resulting in uninteresting responses.
Explaining Relationships Between Scientific Documents
We address the task of explaining relationships between two scientific documents using natural language text.
DeFINE: DEep Factorized INput Token Embeddings for Neural Sequence Modeling
For sequence models with large vocabularies, a majority of network parameters lie in the input and output layers.
SemEval-2019 Task 10: Math Question Answering
Systems were evaluated based on the percentage of correctly answered questions.
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
We introduce a new representation language to model precise operation programs corresponding to each math problem that aim to improve both the performance and the interpretability of the learned models.
Text Generation from Knowledge Graphs with Graph Transformers
Generating texts which express complex ideas spanning multiple sentences requires a structured representation of their content (document plan), but these representations are prohibitively expensive to manually produce.
Ranked #6 on
KG-to-Text Generation
on AGENDA
Pyramidal Recurrent Unit for Language Modeling
We introduce the Pyramidal Recurrent Unit (PRU), which enables learning representations in high dimensional space with more generalization power and fewer parameters.
Data-Driven Methods for Solving Algebra Word Problems
We explore contemporary, data-driven techniques for solving math word problems over recent large-scale datasets.
A Theme-Rewriting Approach for Generating Algebra Word Problems
Texts present coherent stories that have a particular theme or overall setting, for example science fiction or western.
Parsing Algebraic Word Problems into Equations
This paper formalizes the problem of solving multi-sentence algebraic word problems as that of generating and scoring equation trees.
