22 citations · 29 across the 10 of their papers we have counts for
9 papers · 1 filter
CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees
S M Rafiuddin, Atriya Sen
Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…
Hallucination reduction with CASAL: Contrastive Activation Steering For Amortized Learning
Wannan, Yang, Xinchi Qiu +6
Large Language Models (LLMs) exhibit impressive capabilities but often hallucinate, confidently providing incorrect answers instead of admitting ignorance. Prior work has shown tha…
Measuring AI "Slop" in Text
Chantal Shaib, Tuhin Chakrabarty, Diego Garcia-Olano +1
AI "slop" is an increasingly popular term used to describe low-quality AI-generated text, but there is currently no agreed upon definition of this term nor a means to measure its o…
Improving LLM First-Token Predictions in Multiple-Choice Question Answering via Output Prefilling
Silvia Cappelletti, Tobia Poppi, Samuele Poppi +5
Large Language Models (LLMs) are increasingly evaluated on multiple-choice question answering (MCQA) tasks using *first-token probability* (FTP), which selects the answer option wh…
Using Captum to Explain Generative Language Models
Vivek Miglani, Aobo Yang, Aram H. Markosyan +2
Captum is a comprehensive library for model explainability in PyTorch, offering a range of methods from the interpretability literature to enhance users' understanding of PyTorch m…
Intermediate Entity-based Sparse Interpretable Representation Learning
Diego Garcia-Olano, Yasumasa Onoe, Joydeep Ghosh +1
Interpretable entity representations (IERs) are sparse embeddings that are "human-readable" in that dimensions correspond to fine-grained entity types and values are predicted prob…
Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection
Diego Garcia-Olano, Yasumasa Onoe, Joydeep Ghosh
Knowledge-Based Visual Question Answering (KBVQA) is a bi-modal task requiring external world knowledge in order to correctly answer a text question and associated image. Recent si…
Biomedical Interpretable Entity Representations
Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini +3
Pre-trained language models induce dense entity representations that offer strong performance on entity-centric NLP tasks, but such representations are not immediately interpretabl…
Learning Dense Representations for Entity Retrieval
Daniel Gillick, Sayali Kulkarni, Larry Lansing +4
We show that it is feasible to perform entity linking by training a dual encoder (two-tower) model that encodes mentions and entities in the same dense vector space, where candidat…