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Found 10 papers, 1 papers with code
LLMGuard: Guarding Against Unsafe LLM Behavior
Although the rise of Large Language Models (LLMs) in enterprise settings brings new opportunities and capabilities, it also brings challenges, such as the risk of generating inappropriate, biased, or misleading content that violates regulations and can have legal concerns.
Navigating the Structured What-If Spaces: Counterfactual Generation via Structured Diffusion
Generating counterfactual explanations is one of the most effective approaches for uncovering the inner workings of black-box neural network models and building user trust.
"Beware of deception": Detecting Half-Truth and Debunking it through Controlled Claim Editing
To help combat this problem, we have created a comprehensive pipeline consisting of a half-truth detection model and a claim editing model.
DetAIL : A Tool to Automatically Detect and Analyze Drift In Language
The goal of this work is to ensure that machine learning and deep learning-based systems are as trusted as traditional software.
Plug and Play Counterfactual Text Generation for Model Robustness
We also show that the generated counterfactuals from CASPer can be used for augmenting the training data and thereby fixing and making the test model more robust.
TransDrift: Modeling Word-Embedding Drift using Transformer
In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines.
Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text
Aligned with this, we propose a framework GYC, to generate a set of counterfactual text samples, which are crucial for testing these ML systems.
Judging a Book by its Description : Analyzing Gender Stereotypes in the Man Bookers Prize Winning Fiction
The presence of gender stereotypes in many aspects of society is a well-known phenomenon.
Generating Clues for Gender based Occupation De-biasing in Text
Vast availability of text data has enabled widespread training and use of AI systems that not only learn and predict attributes from the text but also generate text automatically.
Bollywood Movie Corpus for Text, Images and Videos
In this work, we have worked with movie data from Wikipedia plots and movie trailers from YouTube.
