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6 papers · 2 filters
LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints
Thomas Palmeira Ferraz, Kartik Mehta, Yu-Hsiang Lin +7
Instruction following is a key capability for LLMs. However, recent studies have shown that LLMs often struggle with instructions containing multiple constraints (e.g. a request to…
LoFTI: Localization and Factuality Transfer to Indian Locales
Sona Elza Simon, Soumen Kumar Mondal, Abhishek Singhania +2
Large language models (LLMs) encode vast amounts of world knowledge acquired via training on large web-scale datasets crawled from the internet. However, these datasets typically e…
Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for Accurate Natural Language Task Modeling
Wrick Talukdar, Anjanava Biswas
While supervised learning models have shown remarkable performance in various natural language processing (NLP) tasks, their success heavily relies on the availability of large-sca…
Question Suggestion for Conversational Shopping Assistants Using Product Metadata
Nikhita Vedula, Oleg Rokhlenko, Shervin Malmasi
Digital assistants have become ubiquitous in e-commerce applications, following the recent advancements in Information Retrieval (IR), Natural Language Processing (NLP) and Generat…
A dataset and benchmark for hospital course summarization with adapted large language models
Asad Aali, Dave Van Veen, Yamin Ishraq Arefeen +9
Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automati…
COBIAS: Assessing the Contextual Reliability of Bias Benchmarks for Language Models
Priyanshul Govil, Hemang Jain, Vamshi Krishna Bonagiri +4
Large Language Models (LLMs) often inherit biases from the web data they are trained on, which contains stereotypes and prejudices. Current methods for evaluating and mitigating th…