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Found 7 papers, 5 papers with code
Towards Reliable Latent Knowledge Estimation in LLMs: In-Context Learning vs. Prompting Based Factual Knowledge Extraction
We propose an approach for estimating the latent knowledge embedded inside large language models (LLMs).
Probing Critical Learning Dynamics of PLMs for Hate Speech Detection
Despite the widespread adoption, there is a lack of research into how various critical aspects of pretrained language models (PLMs) affect their performance in hate speech detection.
Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detection
As hate speech continues to proliferate on the web, it is becoming increasingly important to develop computational methods to mitigate it.
The Art of Embedding Fusion: Optimizing Hate Speech Detection
Hate speech detection is a challenging natural language processing task that requires capturing linguistic and contextual nuances.
Beyond Negativity: Re-Analysis and Follow-Up Experiments on Hope Speech Detection
Health experts assert that hope plays a crucial role in enhancing individuals' physical and mental well-being, facilitating their recovery, and promoting restoration.
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
How do large language models (LLMs) develop and evolve over the course of training?
Ranked #4 on
Language Modelling
on LAMBADA
(Perplexity metric)
Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization
Curbing online hate speech has become the need of the hour; however, a blanket ban on such activities is infeasible for several geopolitical and cultural reasons.
