Table-based Fact Verification
14 papers with code • 1 benchmarks • 2 datasets
Verifying facts given semi-structured data.
TabFact
InfoTabS
Latest papers
Heuristic Heterogeneous Graph Reasoning Networks for Fact Verification
2024-MindSpore-1/Code2
•
•
journal 2023
In this work, we propose heuristic heterogeneous graph reasoning networks (H2GRN) to capture the shared consistent evidence by strengthening associations between linguistic and logical evidence from two perspectives of graph construction and reasoning mechanism.
Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
alibabaresearch/damo-convai
•
•
To alleviate the above challenges, we exploit large language models (LLMs) as decomposers for effective table-based reasoning, which (i) decompose huge evidence (a huge table) into sub-evidence (a small table) to mitigate the interference of useless information for table reasoning; and (ii) decompose complex questions into simpler sub-questions for text reasoning.
PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-training
In particular, on the complex set of TabFact, which contains multiple operations, PASTA largely outperforms the previous state of the art by 4. 7 points (85. 6% vs. 80. 9%), and the gap between PASTA and human performance on the small TabFact test set is narrowed to just 1. 5 points (90. 6% vs. 92. 1%).
ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples
Reasoning over tabular data requires both table structure understanding and a broad set of table reasoning skills.
Binding Language Models in Symbolic Languages
We propose Binder, a training-free neural-symbolic framework that maps the task input to a program, which (1) allows binding a unified API of language model (LM) functionalities to a programming language (e. g., SQL, Python) to extend its grammar coverage and thus tackle more diverse questions, (2) adopts an LM as both the program parser and the underlying model called by the API during execution, and (3) requires only a few in-context exemplar annotations.
Table-based Fact Verification with Self-adaptive Mixture of Experts
thumlp/samoe
•
•
Findings (ACL) 2022
The table-based fact verification task has recently gained widespread attention and yet remains to be a very challenging problem.
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases and question answering over knowledge bases.
Exploring Decomposition for Table-based Fact Verification
arielsho/decomposition-table-reasoning
•
•
Findings (EMNLP) 2021
Fact verification based on structured data is challenging as it requires models to understand both natural language and symbolic operations performed over tables.
Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification
Specifically, we first retrieve logic-level program-like evidence from the given table and statement as supplementary evidence for the table.
Table-based Fact Verification with Salience-aware Learning
luka-group/salience-aware-learning
•
•
Findings (EMNLP) 2021
From one perspective, our system conducts masked salient token prediction to enhance the model for alignment and reasoning between the table and the statement.
