6 papers
Benchmarking the Energy Savings with Speculative Decoding Strategies
Rohit Dutta, Paramita Koley, Soham Poddar +5
Speculative decoding has emerged as an effective method to reduce latency and inference cost of LLM inferences. However, there has been inadequate attention towards the energy requ…
Brevity is the soul of sustainability: Characterizing LLM response lengths
Soham Poddar, Paramita Koley, Janardan Misra +4
A significant portion of the energy consumed by Large Language Models (LLMs) arises from their inference processes; hence developing energy-efficient methods for inference is cruci…
Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models
Soham Poddar, Paramita Koley, Janardan Misra +3
Large language models (LLMs) are increasingly recognized for their exceptional generative capabilities and versatility across various tasks. However, the high inference costs assoc…
Parameter-Efficient Instruction Tuning of Large Language Models For Extreme Financial Numeral Labelling
Subhendu Khatuya, Rajdeep Mukherjee, Akash Ghosh +5
We study the problem of automatically annotating relevant numerals (GAAP metrics) occurring in the financial documents with their corresponding XBRL tags. Different from prior work…
Instruction-Guided Bullet Point Summarization of Long Financial Earnings Call Transcripts
Subhendu Khatuya, Koushiki Sinha, Niloy Ganguly +2
While automatic summarization techniques have made significant advancements, their primary focus has been on summarizing short news articles or documents that have clear structural…
How COVID-19 has Impacted the Anti-Vaccine Discourse: A Large-Scale Twitter Study Spanning Pre-COVID and Post-COVID Era
Soham Poddar, Rajdeep Mukherjee, Subhendu Khatuya +2
The debate around vaccines has been going on for decades, but the COVID-19 pandemic showed how crucial it is to understand and mitigate anti-vaccine sentiments. While the pandemic…