Publications

Do You Know What You Are Talking About? Characterizing Knowledge Relevance For Reliable Retrieval Augmented Generation

Zhuohang Li, Jiaxin Zhang, Chao Yan, Kamalika Das, Sricharan Kumar, Murat Kantarcioglu, Bradley A. Malin (EMNLP’24)  

Towards Knowledge Refinement and Injection for Enhancing Large Language Models

Jiaxin Zhang, Wendi Cui, Yiran Huang, Kamalika Das, Sricharan Kumar (EMNLP’24)

HyQE: Ranking Contexts with Hypothetical Query Embeddings

Weichao Zhou, Jiaxin Zhang, Hilaf Hasson, Anu Singh, Wenchao Li (EMNLP’24)  

Mitigating Hallucination in Fictional Character Role Play

Nafis Sadeq, Zhouhang Xie, Byungkyu Kang, Prarit Lamba, Xiang Gao, Julian McAuley (EMNLP'24)  

Holistic Evaluation of Interleaved Text and Image Generation 

Minqian Liu, Zhiyang Xu, Zihao Lin, Trevor Ashby, Joy Rimchala, Jiaxin Zhang, Lifu Huang (EMNLP’24)

DCR-Consistency: Evaluating and Improving Generation Consistency of Large Language Models via A Divide-Conquer-Reasoning Approach

Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley Malin, Sricharan Kumar (EMNLP’24 - Industry Track) 

Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution

Ankita Sinha, Wendi Cui, Kamalika Das, Jiaxin Zhang (EMNLP’24 - Industry Track)

LLM+Reasoning+Planning for Supporting Incomplete User Queries in Presence of APIs

Sudhir Agarwal, Anu Sreepathy, David H. Alonso, Prarit Lamba (ICLP'24)

Translate-Infer-Compile for Accurate “Text to Plan” using LLMs and Logical Representations

Sudhir Agarwal, Anu Sreepathy (NeSy'24)

Know, Grow, and Protect Net Worth: Using ML for Asset Protection by Preventing Overdraft Fees

Avishek Kumar, Tyson Silver (KDD'24)

RE²: Region-Aware Relation Extraction from Visually Rich Documents

Pritika Ramu, Sijia Wang, Lalla Mouatadid, Joy Rimchala, Lifu Huang (NAACL‘24)

BookSQL: A Large Scale Text-to-SQL Dataset for Accounting Domain

Rahul Kumar, Amar Raja Dibbu, Shrutendra Harsola, Vignesh Subrahmaniam, Ashutosh Modi (NAACL’24)

Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods

Jiaxin Zhang, Kamalika Das, Sricharan Kumar (AISTATS'24)

COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification

Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind, Supratik Mukhopadhyay, Kamalika Das (SDM'24) (Best student poster runner up)

Optimizing Counterfactual-based Analysis of Machine Learning Models Through Databases

Aviv Ben Arie, Daniel Deutch, Nave Frost, Yair Horesh, Idan Meyuhas (EDBT'24)

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, Kamalika Das (EACL'24)

A Typology of Errors for User Utterances in Chatbots

Esmé Manandise, Anu Singh (LREC-COLING'24)

Customizing Language Model Responses with Contrastive In-Context Learning

Xiang Gao, Kamalika Das (AAAI'24)

BBE-LSWCM: A Bootstrapped Ensemble of Long and Short Window Clickstream Models

Arnab Chakraborty, Vikas Raturi, Shrutendra Harsola (CODS-COMAD‘24) (Best Paper Award)

DECDM: Document Enhancement using Cycle-Consistent Diffusion Models

Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Sricharan Kumar (WACV'24)

Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision

Jiaxin Zhang, Zhuohang Li, Kamalika Das, Sricharan Kumar (NeurIPS'23) 

A Divide-Conquer-Reasoning Approach to Consistency Evaluation and Improvement in Blackbox Large Language Models

Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley Malin, Sricharan Kumar (NeurIPS'23 workshop)

SAC³: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check Consistency

Jiaxin Zhang, Zhuohang Li, Kamalika Das, Bradley A. Malin, Sricharan Kumar (EMNLP'23)  

ODEWS: The Overdraft Early Warning System

Avishek Kumar, Tyson Silver (KDD'24)

On the Robustness of Diffusion Inversion in Image Manipulation

Jiaxin Zhang, Kamalika Das, Sricharan Kumar (ICLR'23 workshop)

A Novel Control-Variates Approach for Performative Gradient-Based Learners with Missing Data

Xing Han, Jing Hu, Joydeep Ghosh (IJCNN’23)

Unsupervised Improvement of Factual Knowledge in Language Models

Nafis Sadeq, Byungkyu Kang, Prarit Lamba, Julian McAuley (EACL’23)

Efficient Forecasting of Large-Scale Hierarchical Time Series via Multilevel Clustering

Xing Han, Tongzheng Ren, Jing Hu, Joydeep Ghosh, Nhat Ho. (J. Engg'2023)

CFDB: Machine Learning Model Analysis via Databases of CounterFactuals

Idan Meyuhas, Aviv Ben Arie, Yair Horesh, Daniel Deutch (SIGMOD'22)

Mining Frequent Patterns on Knowledge Graph

Lalla Mouatadid (WSDM'22)

Dynamic Combination of Heterogeneous Models for Hierarchical Time Series

Xing Han, Jung Hu, Joydeep Gosh (ICDMW‘22)

Extracting Domain Terms from Data Model Elements: Task Overview in One Implementation

Esmé Manandise (NLDB'22), 267–278

Assessing the Natural Language Understanding Dilemma of Chatbots: Seeing or not Seeing the Forest for the Trees

Esmé Manandise, Raj Srivastava (Conversations'22)

A Scalable Technique for Weak-Supervised Learning with Domain Constraints

Sudhir Agarwal, Anu Sreepathy, Lalla Mouatadid (NeurIPS'22)

Simultaneously reconciled quantile forecasting of hierarchically related time series

Xing Han, Joydeep Gosh, Sambarta Dasgupta (AISTATS’21)

Categorization of Financial Transactions in QuickBooks

Juan Liu, Lei Pei, Ying Sun, Heather Simpson, Jocelyn Lu, Nhung Ho (KDD'21)

Unknown-box approximation to improve optical character recognition performance

Ayantha Randika, Nilanjan Ray, Xiao Xiao, Allegra Latimer (ICDAR’21)

Explainable AI and Adoption of Financial Algorithmic Advisors: An Experimental Study

Daniel Ben David, Yehezkel S. Resheff, Talia Tron (AIES'21)

Large Scale Personalized Categorization of Financial Transactions

Christopher Lesner, Alexander Ran, Marko Rukonic, Wei Wang (AAAI’19)