Research
Mar 2026
Router-Suggest: Dynamic Routing for Multimodal Auto-Completion in Visually-Grounded Dialogs
EACL 2026 · Industry Track
Defined the Multimodal Auto-Completion (MAC) vision-language task from scratch — task definition, dataset curation, and evaluation protocol. Benchmarked state-of-the-art VLMs (Qwen2-VL, MiniCPM-V, PaliGemma) and proposed Router-Suggest, a dynamic routing framework achieving 2.3×–10× speedup over the best VLM baseline while maintaining near-parity accuracy.
Mar 2026
Chat-Ghosting: Methods for Auto-Completion in Dialog Systems
EACL 2026
Introduced the first comprehensive benchmark for chat-ghosting (predictive text completion in conversations) across 4 public dialog datasets. Proposed an entropy-based dynamic early-stopping mechanism that significantly improves Partial-Precision and TES, making auto-completion practical for real dialog applications.
Apr 2023
Zero-Shot Cross-Lingual QA via Prefix Tuning on mT5
Research project · advised by Prof. Pawan Goyal, CSE, IIT Kharagpur
Investigated parameter-efficient fine-tuning using prefix tuning on mT5 for zero-shot cross-lingual question answering. Demonstrated competitive transfer performance with under 1% trainable parameters compared to full fine-tuning.
Apr 2023
Efficient Product Embeddings & Semantic Search Engine
Research project · advised by Prof. B. Adhikari, Mathematics, IIT Kharagpur
Showed BERT contextual embeddings outperform Word2Vec and GloVe by 10× on product retrieval across 14,000 Amazon products. Built a semantic search engine with 3-D TensorFlow Embedding Projector visualisation for interpretability.