11 citations · 50 across the 24 of their papers we have counts for
5 papers · 2 filters
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation
Tianxing He, Jingyu Zhang, Tianle Wang +4
In this work, we explore a useful but often neglected methodology for robustness analysis of text generation evaluation metrics: stress tests with synthetic data. Basically, we des…
Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation
Melanie Sclar, Peter West, Sachin Kumar +2
We present Referee, a novel framework for sentence summarization that can be trained reference-free (i.e., requiring no gold summaries for supervision), while allowing direct contr…
SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control
Xiaochuang Han, Sachin Kumar, Yulia Tsvetkov
Despite the growing success of diffusion models in continuous-valued domains (e.g., images), similar efforts for discrete domains such as text have yet to match the performance of…
Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey
Sachin Kumar, Vidhisha Balachandran, Lucille Njoo +2
Recent advances in the capacity of large language models to generate human-like text have resulted in their increased adoption in user-facing settings. In parallel, these improveme…
Gradient-Based Constrained Sampling from Language Models
Sachin Kumar, Biswajit Paria, Yulia Tsvetkov
Large pretrained language models generate fluent text but are notoriously hard to controllably sample from. In this work, we study constrained sampling from such language models: g…