9 citations · 23 across the 16 of their papers we have counts for
16 papers
GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization
Disha Sheshanarayana, Rajat Subhra Pal, Manjira Sinha +1
The growing deployment of large language models (LLMs) makes per-request routing essential for balancing response quality and computational cost across heterogeneous model pools. C…
Thinking in Latents: Adaptive Anchor Refinement for Implicit Reasoning in LLMs
Disha Sheshanarayana, Rajat Subhra Pal, Manjira Sinha +1
Token-level Chain-of-Thought (CoT) prompting has become a standard way to elicit multi-step reasoning in large language models (LLMs), especially for mathematical word problems. Ho…
Decoding Plastic Toxicity: An Intelligent Framework for Conflict-Aware Relational Metapath Extraction from Scientific Abstracts
Sudeshna Jana, Manjira Sinha, Tirthankar Dasgupta
The widespread use of plastics and their persistence in the environment have led to the accumulation of micro- and nano-plastics across air, water, and soil, posing serious health…
StayLTC: A Cost-Effective Multimodal Framework for Hospital Length of Stay Forecasting
Sudeshna Jana, Manjira Sinha, Tirthankar Dasgupta
Accurate prediction of Length of Stay (LOS) in hospitals is crucial for improving healthcare services, resource management, and cost efficiency. This paper presents StayLTC, a mult…
Mapping Patient Trajectories: Understanding and Visualizing Sepsis Prognostic Pathways from Patients Clinical Narratives
Sudeshna Jana, Tirthankar Dasgupta, Lipika Dey
In recent years, healthcare professionals are increasingly emphasizing on personalized and evidence-based patient care through the exploration of prognostic pathways. To study this…
Leveraging the Fisher randomization test using confidence distributions: inference, combination and fusion learning
Xiaokang Luo, Tirthankar Dasgupta, Minge Xie +1
The flexibility and wide applicability of the Fisher randomization test (FRT) makes it an attractive tool for assessment of causal effects of interventions from modern-day randomiz…