Search Results for author:
Found 9 papers, 2 papers with code
Acknowledgement Entity Recognition in CORD-19 Papers
We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to 50–60% of named entities are actually acknowledged.
Inside the echo chamber: Linguistic underpinnings of misinformation on Twitter
Social media users drive the spread of misinformation online by sharing posts that include erroneous information or commenting on controversial topics with unsubstantiated arguments often in earnest.
"Confidently Nonsensical?'': A Critical Survey on the Perspectives and Challenges of 'Hallucinations' in NLP
We investigate how hallucination in large language models (LLM) is characterized in peer-reviewed literature using a critical examination of 103 publications across NLP research.
Can Large Language Models Discern Evidence for Scientific Hypotheses? Case Studies in the Social Sciences
Hypothesis formulation and testing are central to empirical research.
A Study on Reproducibility and Replicability of Table Structure Recognition Methods
We then examine replicability using a dataset similar to the original as well as a new dataset, GenTSR, consisting of 386 annotated tables extracted from scientific papers.
A prototype hybrid prediction market for estimating replicability of published work
We present a prototype hybrid prediction market and demonstrate the avenue it represents for meaningful human-AI collaboration.
A Synthetic Prediction Market for Estimating Confidence in Published Work
Explainably estimating confidence in published scholarly work offers opportunity for faster and more robust scientific progress.
Design and Analysis of a Synthetic Prediction Market using Dynamic Convex Sets
We show that under certain assumptions on the underlying geometry, the resulting synthetic prediction market can be used to arbitrarily closely approximate a binary function defined on a set of input data.
A Semantics-based Approach to Disclosure Classification in User-Generated Online Content
As users engage in public discourse, the rate of voluntarily disclosed personal information has seen a steep increase.
