544 citations · 564 across the 14 of their papers we have counts for
11 papers · 1 filter
Sequential Harmful Shift Detection Without Labels
Salim I. Amoukou, Tom Bewley, Saumitra Mishra +3
We introduce a novel approach for detecting distribution shifts that negatively impact the performance of machine learning models in continuous production environments, which requi…
Interpretable LLM-based Table Question Answering
Giang Nguyen, Ivan Brugere, Shubham Sharma +3
Interpretability in Table Question Answering (Table QA) is critical, especially in high-stakes domains like finance and healthcare. While recent Table QA approaches based on Large…
Interpreting Language Reward Models via Contrastive Explanations
Junqi Jiang, Tom Bewley, Saumitra Mishra +2
Reward models (RMs) are a crucial component in the alignment of large language models' (LLMs) outputs with human values. RMs approximate human preferences over possible LLM respons…
Graphusion: A RAG Framework for Knowledge Graph Construction with a Global Perspective
Rui Yang, Boming Yang, Aosong Feng +7
Knowledge Graphs (KGs) are crucial in the field of artificial intelligence and are widely used in downstream tasks, such as question-answering (QA). The construction of KGs typical…
Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP Education
Rui Yang, Boming Yang, Sixun Ouyang +6
Knowledge graphs (KGs) are crucial in the field of artificial intelligence and are widely applied in downstream tasks, such as enhancing Question Answering (QA) systems. The constr…
Quantifying Prediction Consistency Under Fine-Tuning Multiplicity in Tabular LLMs
Faisal Hamman, Pasan Dissanayake, Saumitra Mishra +2
Fine-tuning LLMs on tabular classification tasks can lead to the phenomenon of fine-tuning multiplicity where equally well-performing models make conflicting predictions on the sam…