343 citations · 491 across the 34 of their papers we have counts for
9 papers · 1 filter
Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates
Xiaochuang Han, Yulia Tsvetkov
Among the most critical limitations of deep learning NLP models are their lack of interpretability, and their reliance on spurious correlations. Prior work proposed various approac…
Can Machines Learn Morality? The Delphi Experiment
Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula +12
As AI systems become increasingly powerful and pervasive, there are growing concerns about machines' morality or a lack thereof. Yet, teaching morality to machines is a formidable…
Improving Span Representation for Domain-adapted Coreference Resolution
Nupoor Gandhi, Anjalie Field, Yulia Tsvetkov
Recent work has shown fine-tuning neural coreference models can produce strong performance when adapting to different domains. However, at the same time, this can require a large a…
Controlled Text Generation as Continuous Optimization with Multiple Constraints
Sachin Kumar, Eric Malmi, Aliaksei Severyn +1
As large-scale language model pretraining pushes the state-of-the-art in text generation, recent work has turned to controlling attributes of the text such models generate. While m…
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
Zirui Wang, Jiahui Yu, Adams Wei Yu +3
With recent progress in joint modeling of visual and textual representations, Vision-Language Pretraining (VLP) has achieved impressive performance on many multimodal downstream ta…
Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation
Prakhar Gupta, Yulia Tsvetkov, Jeffrey P. Bigham
Open-domain neural dialogue models have achieved high performance in response ranking and evaluation tasks. These tasks are formulated as a binary classification of responses given…
DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues
Rishabh Joshi, Vidhisha Balachandran, Shikhar Vashishth +2
To successfully negotiate a deal, it is not enough to communicate fluently: pragmatic planning of persuasive negotiation strategies is essential. While modern dialogue agents excel…
Simple and Efficient ways to Improve REALM
Vidhisha Balachandran, Ashish Vaswani, Yulia Tsvetkov +1
Dense retrieval has been shown to be effective for retrieving relevant documents for Open Domain QA, surpassing popular sparse retrieval methods like BM25. REALM (Guu et al., 2020)…
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov
Modern summarization models generate highly fluent but often factually unreliable outputs. This motivated a surge of metrics attempting to measure the factuality of automatically g…