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Found 11 papers, 7 papers with code
COLD: Causal reasOning in cLosed Daily activities
Large Language Models (LLMs) have shown state-of-the-art performance in a variety of tasks, including arithmetic and reasoning; however, to gauge the intellectual capabilities of LLMs, causal reasoning has become a reliable proxy for validating a general understanding of the mechanics and intricacies of the world similar to humans.
Towards Robust Evaluation of Unlearning in LLMs via Data Transformations
Large Language Models (LLMs) have shown to be a great success in a wide range of applications ranging from regular NLP-based use cases to AI agents.
iSign: A Benchmark for Indian Sign Language Processing
To bridge this gap, in this work, we propose iSign: a benchmark for Indian Sign Language (ISL) Processing.
IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning
Legal systems worldwide are inundated with exponential growth in cases and documents.
ISLTranslate: Dataset for Translating Indian Sign Language
To the best of our knowledge, it is the largest translation dataset for continuous Indian Sign Language.
U-CREAT: Unsupervised Case Retrieval using Events extrAcTion
To further promote research in PCR, in this paper, we propose a new large benchmark (in English) for the PCR task: IL-PCR (Indian Legal Prior Case Retrieval) corpus.
ScriptWorld: Text Based Environment For Learning Procedural Knowledge
Text-based games provide a framework for developing natural language understanding and commonsense knowledge about the world in reinforcement learning based agents.
SemEval 2023 Task 6: LegalEval - Understanding Legal Texts
LegalEval task has three sub-tasks: Task-A (Rhetorical Roles Labeling) is about automatically structuring legal documents into semantically coherent units, Task-B (Legal Named Entity Recognition) deals with identifying relevant entities in a legal document and Task-C (Court Judgement Prediction with Explanation) explores the possibility of automatically predicting the outcome of a legal case along with providing an explanation for the prediction.
Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environments
In order to process the multimodal information automatically and use it for an end application, Multimodal Representation Learning (MRL) has emerged as an active area of research in recent times.
COGMEN: COntextualized GNN based Multimodal Emotion recognitioN
Emotions are an inherent part of human interactions, and consequently, it is imperative to develop AI systems that understand and recognize human emotions.
Ranked #3 on
Multimodal Emotion Recognition
on IEMOCAP-4
Shapes of Emotions: Multimodal Emotion Recognition in Conversations via Emotion Shifts
The proposed emotion-shift component is modular and can be added to any existing multimodal ERC model (with a few modifications).
