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20242026
most citedA Survey of Transformer-based Language Models with Focus on Efficiency

9 citations · 10 across the 10 of their papers we have counts for

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cs.CL2026

MMTClinic: Multimodal, Multilingual Time Series Question Answering and Reasoning Benchmark for Clinical Domain

Sourav Malakar, Harshit Nigam, Akash Ghosh +4

Time-series data in clinical settings is crucial for capturing dynamic changes in a patient's health over time, enabling timely diagnosis, personalized treatment, and early detecti…

cs.CL2026

Latent Performance Profiling of Large Language Models

Tanmoy Chakraborty, Ayan Sengupta, Suparna Bhattacharya +7

Large language models (LLMs) frequently achieve impressive scores on standardized benchmarks, yet accuracy alone offers a limited view of their capabilities. Evaluating open-source…

cs.CL2024★ 1 cited

BEExformer: A Fast Inferencing Binarized Transformer with Early Exits

Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti

Large Language Models (LLMs) based on transformers achieve cutting-edge results on a variety of applications. However, their enormous size and processing requirements hinder deploy…

cs.CL2024

TexIm FAST: Text-to-Image Representation for Semantic Similarity Evaluation using Transformers

Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti

One of the principal objectives of Natural Language Processing (NLP) is to generate meaningful representations from text. Improving the informativeness of the representations has l…

cs.CL2024★ 9 cited

A Survey of Transformer-based Language Models with Focus on Efficiency

Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti

The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (NLP), thereby intensifying the demand f…