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Found 12 papers, 2 papers with code
FactCheck Editor: Multilingual Text Editor with End-to-End fact-checking
We introduce 'FactCheck Editor', an advanced text editor designed to automate fact-checking and correct factual inaccuracies.
The Surprising Effectiveness of Rankers Trained on Expanded Queries
In our extensive experiments on the DL-Hard dataset, we find that a principled query performance based scoring method using base and specialized ranker offers a significant improvement of up to 25% on the passage ranking task and up to 48. 4% on the document ranking task when compared to the baseline performance of using original queries, even outperforming SOTA model.
QuanTemp: A real-world open-domain benchmark for fact-checking numerical claims
This addresses the challenge of verifying real-world numerical claims, which are complex and often lack precise information, not addressed by existing works that mainly focus on synthetic claims.
Surprising Efficacy of Fine-Tuned Transformers for Fact-Checking over Larger Language Models
In this paper, we explore the challenges associated with establishing an end-to-end fact-checking pipeline in a real-world context, covering over 90 languages.
PKG API: A Tool for Personal Knowledge Graph Management
Personal knowledge graphs (PKGs) offer individuals a way to store and consolidate their fragmented personal data in a central place, improving service personalization while maintaining full user control.
Context Aware Query Rewriting for Text Rankers using LLM
We find that there are two inherent limitations of using LLMs as query re-writers -- concept drift when using only queries as prompts and large inference costs during query processing.
Query Understanding in the Age of Large Language Models
Querying, conversing, and controlling search and information-seeking interfaces using natural language are fast becoming ubiquitous with the rise and adoption of large-language models (LLM).
Extreme Classification for Answer Type Prediction in Question Answering
In this paper, we propose use of extreme multi-label classification using Transformer models (XBERT) by clustering KG types using structural and semantic features based on question text.
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals
We introduce SparcAssist, a general-purpose risk assessment tool for the machine learning models trained for language tasks.
Semantic Answer Type Prediction using BERT: IAI at the ISWC SMART Task 2020
This paper summarizes our participation in the SMART Task of the ISWC 2020 Challenge.
BRENDA: Browser Extension for Fake News Detection
Misinformation such as fake news has drawn a lot of attention in recent years.
A Comparative Study for Unsupervised Network Representation Learning
However, there is no common ground for systematic comparison of embeddings to understand their behavior for different graphs and tasks.
