5 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…
Utilising Large Language Models for Generating Effective Counter Arguments to Anti-Vaccine Tweets
Utsav Dhanuka, Soham Poddar, Saptarshi Ghosh
In an era where public health is increasingly influenced by information shared on social media, combatting vaccine skepticism and misinformation has become a critical societal goal…
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…
ICPR 2024 Competition on Multilingual Claim-Span Identification
Soham Poddar, Biswajit Paul, Moumita Basu +1
A lot of claims are made in social media posts, which may contain misinformation or fake news. Hence, it is crucial to identify claims as a first step towards claim verification. G…