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Found 6 papers, 4 papers with code
PRobELM: Plausibility Ranking Evaluation for Language Models
This paper introduces PRobELM (Plausibility Ranking Evaluation for Language Models), a benchmark designed to assess language models' ability to discern more plausible from less plausible scenarios through their parametric knowledge.
Language Models as Hierarchy Encoders
Interpreting hierarchical structures latent in language is a key limitation of current language models (LMs).
DIALIGHT: Lightweight Multilingual Development and Evaluation of Task-Oriented Dialogue Systems with Large Language Models
We present DIALIGHT, a toolkit for developing and evaluating multilingual Task-Oriented Dialogue (ToD) systems which facilitates systematic evaluations and comparisons between ToD systems using fine-tuning of Pretrained Language Models (PLMs) and those utilising the zero-shot and in-context learning capabilities of Large Language Models (LLMs).
Zero-Shot Fact-Checking with Semantic Triples and Knowledge Graphs
Despite progress in automated fact-checking, most systems require a significant amount of labeled training data, which is expensive.
Varifocal Question Generation for Fact-checking
Our method outperforms previous work on a fact-checking question generation dataset on a wide range of automatic evaluation metrics.
Can Pretrained Language Models (Yet) Reason Deductively?
Acquiring factual knowledge with Pretrained Language Models (PLMs) has attracted increasing attention, showing promising performance in many knowledge-intensive tasks.
