Papers by Rahul Garg
Just KIDDIN’ : Knowledge Infusion and Distillation for Detection of INdecent Memes (2025.findings-acl)
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| Challenge: | Existing approaches to detect toxicity in online multimodal environments require common-sense reasoning and contextual awareness. |
| Approach: | They propose a hybrid neurosymbolic framework that unifies distillation of implicit contextual knowledge from Large Vision-Language Models and infusion of explicit relational semantics through sub-graphs from Knowledge Graphs. |
| Outcome: | The proposed framework outperforms state-of-the-art models on two datasets with improvements of 0.5%, and 10.6% in HatefulMemes Benchmark. |
CFL: Causally Fair Language Models Through Token-level Attribute Controlled Generation (2023.findings-acl)
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| Challenge: | Existing methods to control attributes of Language Models (LMs) for text generation are not safe, as toxicity and bias goals are opposed to each other. |
| Approach: | They propose a method to control the attributes of Language Models (LMs) for the text generation task using Causal Average Treatment Effect (ATE) scores and counterfactual augmentation. |
| Outcome: | The proposed architecture achieves state of the art performance for toxic degeneration, which are computed using Real Toxicity Prompts. |
SandhiKosh: A Benchmark Corpus for Evaluating Sanskrit Sandhi Tools (L18-1)
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| Challenge: | Several important texts which are of interest to people all over the world were written in Sanskrit. |
| Approach: | They develop a Sanskrit benchmark to evaluate the completeness and accuracy of tools . they use three most prominent tools to evaluate their completeness . |
| Outcome: | The proposed tools have substantial scope for improvement and are available to researchers worldwide. |