Papers with AI techniques
TOI-CNN: a Solution of Information Extraction on Chinese Insurance Policy (N19-2)
Copied to clipboard
| Challenge: | Existing methods for Element Tagging on insurance policies can be used to streamline manual review of hundreds of contracts. |
| Approach: | They propose a text-of-interest convolutional neural network (TOI-CNN) to replace traditional pooling layer for processing nested phrasal or clausal elements in insurance policies. |
| Outcome: | The proposed method can automatically convert a massive amount of insurance policies into structural archives for management and comparison. |
Automatic Scene-based Topic Channel Construction System for E-Commerce (2022.emnlp-industry)
Copied to clipboard
| Challenge: | Recent scene marketing has proved effective for offline shopping. |
| Approach: | They propose a novel product form, scene-based topic channel, which consists of a list of diverse products belonging to the same usage scenario and a topic title that describes the scenario with marketing words. |
| Outcome: | The proposed system can be automated and tested on a real-world e-commerce recommendation platform. |
Advanced Messaging Platform (AMP): Pipeline for Automated Enterprise Email Processing (2025.acl-industry)
Copied to clipboard
Simerjot Kaur, Charese Smiley, Keshav Ramani, Elena Kochkina, Mathieu Sibue, Samuel Mensah, Pietro Totis, Cecilia Tilli, Toyin Aguda, Daniel Borrajo, Manuela Veloso
| Challenge: | a lack of publicly available datasets for training and benchmarking limits current AI techniques' effectiveness in industry-specific applications. |
| Approach: | They propose an email automation pipeline that automates email response generation at scale in real-world enterprise settings. |
| Outcome: | The proposed pipeline automates email response generation at scale in real-world environments. |
A Joint Learning Framework for Restaurant Survival Prediction and Explanation (2022.emnlp-main)
Copied to clipboard
| Challenge: | Recent advances in deep learning have various models that research reviews and interactions for different kinds of tasks, such as predicting restaurant survival. |
| Approach: | They propose a joint learning framework for explainable restaurant survival prediction based on multi-modal data of user-restaurant interactions and users’ textual reviews. |
| Outcome: | The proposed framework improves on two datasets showing that it can model restaurant interactions and users’ textual reviews. |
Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal Reasoning (L18-1)
Copied to clipboard
Jinyoung Yeo, Gyeongbok Lee, Gengyu Wang, Seungtaek Choi, Hyunsouk Cho, Reinald Kim Amplayo, Seung-won Hwang
| Challenge: | Existing methods for evaluating plausibility of events are focused on measuring causal dependency between events or actions. |
| Approach: | They propose a task to identify the more plausible alternative with their commonsense causal context. |
| Outcome: | The proposed task is based on a visual COPA dataset with 380 questions and over 1K images with various topics. |
Causality-Guided Multi-Memory Interaction Network for Multivariate Stock Price Movement Prediction (2023.acl-long)
Copied to clipboard
| Challenge: | Existing models for stock price movement prediction use auxiliary data, but we assume other stocks should be utilized as auxiliary information to enhance performance. |
| Approach: | They propose a Causality-guided multi-memory interaction network for stock movement prediction which transforms basic attention into Causal Attention by calculating transfer entropy between multivariate stocks. |
| Outcome: | The proposed model outperforms existing models on three real-world datasets from the U.S. and Chinese markets. |
Learning by Analogy: Diverse Questions Generation in Math Word Problem (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for solving math word problem (MWP) use shortcut learning to train solvers based on samples with a single question. |
| Approach: | They propose to generate diverse yet consistent questions from a common scenario . they then feed the equations to a question generator to obtain the diverse questions . their method leads to performance improvement on the current benchmark Math23K . |
| Outcome: | The proposed method generates diverse yet consistent questions with a variety of equations and questions . it improves on the current benchmark, which is based on the proposed method . |
Release of Pre-Trained Models for the Japanese Language (2024.lrec-main)
Copied to clipboard
Kei Sawada, Tianyu Zhao, Makoto Shing, Kentaro Mitsui, Akio Kaga, Yukiya Hono, Toshiaki Wakatsuki, Koh Mitsuda
| Challenge: | democratization of AI aims to create a world where everyone can use AI . pre-trained models with high performance in Japanese are lagging in non-English-speaking communities . |
| Approach: | et al. released large-scale pre-trained models trained on large-data to improve access to AI . authors say the models are more accurate and more accurate than those trained in the English language . e-mail protected: email protected. |
| Outcome: | a new study shows that pre-trained models specialized for Japanese can achieve high performance in Japanese tasks. |