87 citations · 209 across the 38 of their papers we have counts for
6 papers · 1 filter
CATS: A Pragmatic Chinese Answer-to-Sequence Dataset with Large Scale and High Quality
Liang Li, Ruiying Geng, Chengyang Fang +6
There are three problems existing in the popular data-to-text datasets. First, the large-scale datasets either contain noise or lack real application scenarios. Second, the dataset…
History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling
Hao Sun, Yang Li, Liwei Deng +6
Context information modeling is an important task in conversational KBQA. However, existing methods usually assume the independence of utterances and model them in isolation. In th…
Iterative Forward Tuning Boosts In-Context Learning in Language Models
Jiaxi Yang, Binyuan Hui, Min Yang +5
Despite the advancements in in-context learning (ICL) for large language models (LLMs), current research centers on specific prompt engineering, such as demonstration selection, wi…
Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs
Jinyang Li, Binyuan Hui, Ge Qu +15
Text-to-SQL parsing, which aims at converting natural language instructions into executable SQLs, has gained increasing attention in recent years. In particular, Codex and ChatGPT…
Plan-then-Seam: Towards Efficient Table-to-Text Generation
Liang Li, Ruiying Geng, Chengyang Fang +4
Table-to-text generation aims at automatically generating text to help people conveniently obtain salient information in tables. Recent works explicitly decompose the generation pr…
Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
Yunhu Ye, Binyuan Hui, Min Yang +3
Table-based reasoning has shown remarkable progress in combining deep models with discrete reasoning, which requires reasoning over both free-form natural language (NL) questions a…