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Sambaran Bandyopadhyay

11 accepted papers

2026

RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation

ICML 2026poster

Multi-hop Question Answering over Knowledge Graphs faces a critical challenge: traditional retrieve-then-read pipelines break differentiability, preventing the retriever from learning to bridge the semantic gap where intermediate nodes lack lexical overlap with the query. To address this, we propose…

Cited by 0SourceScholar
2025

Deep Submodular Optimization and LLM for Multimodal Content Extraction and Automatic Poster Generation from Long Document

AAAI 2025technical

A poster from a long input document can be considered as a one-page easy-to-read multimodal (text and images) summary presented on a nice template with good design elements. Automatic transformation of a long document into a poster is a very less studied but challenging task. It involves content sum…

2025

Infogen: Generating Complex Statistical Infographics from Documents

ACL 2025long

Statistical infographics are powerful tools that simplify complex data into visually engaging and easy-to-understand formats. Despite advancements in AI, particularly with LLMs, existing efforts have been limited to generating simple charts, with no prior work addressing the creation of complex info…

Cited by 0SourcePDFScholar
2025

Language Models of Code Are Few-Shot Planners and Reasoners for Multi-Document Summarization with Attribution

AAAI 2025technical

Document summarization has greatly benefited from advances in large language models (LLMs). In real-world situations, summaries often need to be generated from multiple documents with diverse sources and authors, lacking a clear information flow. Naively concatenating these documents and generating…

Cited by 0SourcePDFScholar
2025

Leveraging Self-Attention for Input-Dependent Soft Prompting in LLMs

ACL 2025short

The performance of large language models in domain-specific tasks necessitates fine-tuning, which is computationally expensive and technically challenging. This paper focuses on parameter-efficient fine-tuning using soft prompting, a promising approach that adapts pre-trained models to downstream ta…

Cited by 0SourcePDFScholar
2024

Is This a Bad Table? A Closer Look at the Evaluation of Table Generation from Text

EMNLP 2024main

Understanding whether a generated table is of good quality is important to be able to use it in creating or editing documents using automatic methods. In this work, we underline that existing measures for table quality evaluation fail to capture the overall semantics of the tables, and sometimes unf…

Cited by 1SourcePDFScholar
2024

Presentations are not always linear! GNN meets LLM for Text Document-to-Presentation Transformation with Attribution

EMNLP 2024finding

Automatically generating a presentation from the text of a long document is a challenging and useful problem. In contrast to a flat summary, a presentation needs to have a better and non-linear narrative, i.e., the content of a slide can come from different and non-contiguous parts of the given docu…

Cited by 2SourcePDFScholar
2022

Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture

IJCAI 2022poster

Soil moisture is an important component of precision agriculture as it directly impacts the growth and quality of vegetation. Forecasting soil moisture is essential to schedule the irrigation and optimize the use of water. Physics based soil moisture models need rich features and heavy computation w…

2022

Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network

IJCAI 2022poster

Monolithic software encapsulates all functional capabilities into a single deployable unit. But managing it becomes harder as the demand for new functionalities grow. Microservice architecture is seen as an alternative as it advocates building an application through a set of loosely coupled small se…

2021

Graph Neural Network to Dilute Outliers for Refactoring Monolith Application

AAAI 2021technical

Microservices are becoming the defacto design choice for software architecture. It involves partitioning the software components into finer modules such that the development can happen independently. It also provides natural benefits when deployed on the cloud since resources can be allocated dynami…

2021

Unsupervised constrained community detection via self-expressive graph neural network

UAI 2021poster

Graph neural networks (GNNs) are able to achieve promising performance on multiple graph downstream tasks such as node classification and link prediction. Comparatively lesser work has been done to design GNNs which can operate directly for community detection on graphs. Traditionally, GNNs are trai…