DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles

A crucial component in the curation of KB for a scientific domain (e.g., materials science, foods & nutrition, fuels) is information extraction from tables in the domain's published research articles. To facilitate research in this direction, we define a novel NLP task of extracting compositions of materials (e.g., glasses) from tables in materials science papers. The task involves solving several challenges in concert, such as tables that mention compositions have highly varying structures; text in captions and full paper needs to be incorporated along with data in tables; and regular languages for numbers, chemical compounds and composition expressions must be integrated into the model. We release a training dataset comprising 4,408 distantly supervised tables, along with 1,475 manually annotated dev and test tables. We also present a strong baseline DISCOMAT, that combines multiple graph neural networks with several task-specific regular expressions, features, and constraints. We show that DISCOMAT outperforms recent table processing architectures by significant margins.Comment: Accepted long paper at ACL 2023 (https://2023.aclweb.org/program/accepted_main_conference/

AutoMix: Automatically Mixing Language Models

Large language models (LLMs) are now available in various sizes and configurations from cloud API providers. While this diversity offers a broad spectrum of choices, effectively leveraging the options to optimize computational cost and performance remains challenging. In this work, we present AutoMix, an approach that strategically routes queries to larger LMs, based on the approximate correctness of outputs from a smaller LM. Central to AutoMix is a few-shot self-verification mechanism, which estimates the reliability of its own outputs without requiring training. Given that verifications can be noisy, we employ a meta verifier in AutoMix to refine the accuracy of these assessments. Our experiments using LLAMA2-13/70B, on five context-grounded reasoning datasets demonstrate that AutoMix surpasses established baselines, improving the incremental benefit per cost by up to 89%. Our code and data are available at https://github.com/automix-llm/automix.Comment: The first two authors contributed equally. Work started and partly done during Aman's internship at Google. This version adds results on mixing 3 models, and will be presented at the workshop on robustness of zero/few-shot learning in foundation models, Neurips 202

Susac′s syndrome: First from India and youngest in the world

A two and half year old female was admitted at the emergency room suffering from gradually worsening headache followed by nausea. The child presented with reduced level of consciousness and bilateral hypoacusis. The patient was lethargic. Ophthalmic examination showed branch retinal artery occlusion (BRAO). This finding was crucial to the diagnosis of Susac′s syndrome (SS), a rare autoimmune disease characterized by, endotheliopathy of retina, encephalic tissues and cochlea. Magnetic resonance imaging of the brain also showed typical features. Thorough blood investigations did not reveal any other abnormality. Patient was treated with immunosuppressive to prevent her from developing severe sequelae of this disease. The child showed dramatic improvement in her systemic condition within 48 h of starting the treatment. This is the youngest ever and first case report from India

An unusual case of self-inflicted multiple needles injuries to eye

Self-inflicted eye injuries among psychiatric patients are rare but important group of ophthalmic conditions that require close cooperation between different medical specialties to ensure optimum care of the severely disturbed patient. They have been associated with a variety of disorders, including paranoid schizophrenia, drug-induced psychosis, obsessive-compulsive disorder, depression, mental retardation, and ritualistic behavior. It has been described in both adults and children, but occurs most commonly in young adults with acute or chronic psychoses