Update README.md

README.md

@@ -8,7 +8,7 @@ library_name: peft
 
 These models are trained to generate neutral (noslang, wordnet, oxford) and biased (slang, all), stance-aware definitions. 
 
-These adapters should be used together with the base model *unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit* and requires *unsloth* installation. 
+These adapters should be used together with the base model *unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit* and require *unsloth* installation. 
 
 
 The models are instruction-tuned on the  dictionary data:
@@ -36,7 +36,7 @@ The models expect a usage example and a keyword as input:
 - keyword = "death penalty"
 - example usage (argument) = "As long as death penalty is kept, this confirms that our society is founded on violence."
 
-While we tested the models on the argumentative data to test their potential to produce stance-aware definitions, they can be used for a general definition generation task for various contexts.
+While we tested the models on the argumentative data to explore their potential to produce stance-aware definitions, they can be used for a general definition generation task for various contexts.
 If you want to generate neutral definitions, avoid using slang- and all- models, these models aim to capture contextual bias that reflects the attitude of the author (pro, contra) towards the keyword. 
 
 The following code can be used for the definition generation task:
@@ -126,6 +126,9 @@ for name, template in PROMPTS.items():
 The best model for the general definition generation task is oxford-llama. The lower plausibility score for slang- and all- models means the definitions are biased. These models can be further used to explore the generation of 
 contextual definitions that capture stance-related bias (pro or contra the keyword). 
 
+The plausibility score is based on human annotations.
+
+
 |   Model           | BERTScoreF1 [%]                |   Plausibility [%]  |
 |-------------------|--------------------------|--------------|
 | LT3/definitions-oxford-llama-8B-instruct        | 88.2                   | 84.5      |
@@ -139,7 +142,7 @@ contextual definitions that capture stance-related bias (pro or contra the keywo
 
 ### BibTeX entry and citation info
 
-If you would like to use or cite our paper or model, feel free to use the following BibTeX code:
+If you use our models, feel free to copy the following BibTeX code to cite the paper:
 
 ```bibtex
 @inproceedings{evgrafova-etal-2025-stance,