18 citations · 22 across the 12 of their papers we have counts for
7 papers · 2 filters
Principled Gradient-based Markov Chain Monte Carlo for Text Generation
Li Du, Afra Amini, Lucas Torroba Hennigen +4
Recent papers have demonstrated the possibility of energy-based text generation by adapting gradient-based sampling algorithms, a paradigm of MCMC algorithms that promises fast con…
Assessing Large Language Models on Climate Information
Jannis Bulian, Mike S. Schäfer, Afra Amini +8
As Large Language Models (LLMs) rise in popularity, it is necessary to assess their capability in critically relevant domains. We present a comprehensive evaluation framework, grou…
Which Spurious Correlations Impact Reasoning in NLI Models? A Visual Interactive Diagnosis through Data-Constrained Counterfactuals
Robin Chan, Afra Amini, Mennatallah El-Assady
We present a human-in-the-loop dashboard tailored to diagnosing potential spurious features that NLI models rely on for predictions. The dashboard enables users to generate diverse…
Hexatagging: Projective Dependency Parsing as Tagging
Afra Amini, Tianyu Liu, Ryan Cotterell
We introduce a novel dependency parser, the hexatagger, that constructs dependency trees by tagging the words in a sentence with elements from a finite set of possible tags. In con…
Structured Voronoi Sampling
Afra Amini, Li Du, Ryan Cotterell
Gradient-based sampling algorithms have demonstrated their effectiveness in text generation, especially in the context of controlled text generation. However, there exists a lack o…
Linear-Time Modeling of Linguistic Structure: An Order-Theoretic Perspective
Tianyu Liu, Afra Amini, Mrinmaya Sachan +1
Tasks that model the relation between pairs of tokens in a string are a vital part of understanding natural language. Such tasks, in general, require exhaustive pair-wise compariso…
In-Context Probing: Toward Building Robust Classifiers via Probing Large Language Models
Afra Amini, Massimiliano Ciaramita
Large language models are able to learn new tasks in context, where they are provided with instructions and a few annotated examples. However, the effectiveness of in-context learn…