activity
20162024
most citedCombining Modular Skills in Multitask Learning

17 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

A Compositional Typed Semantics for Universal Dependencies

Laurestine Bradford, Timothy John O'Donnell, Siva Reddy

Languages may encode similar meanings using different sentence structures. This makes it a challenge to provide a single set of formal rules that can derive meanings from sentences…

cs.CL2024

When does word order matter and when doesn't it?

Xuanda Chen, Timothy O'Donnell, Siva Reddy

Language models (LMs) may appear insensitive to word order changes in natural language understanding (NLU) tasks. In this paper, we propose that linguistic redundancy can explain t…

cs.CL20231 cited

MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations

Arkil Patel, Satwik Bhattamishra, Siva Reddy +1

Humans possess a remarkable ability to assign novel interpretations to linguistic expressions, enabling them to learn new words and understand community-specific connotations. Howe…

cs.LG202217 cited

Combining Modular Skills in Multitask Learning

Edoardo M. Ponti, Alessandro Sordoni, Yoshua Bengio +1

A modular design encourages neural models to disentangle and recombine different facets of knowledge to generalise more systematically to new tasks. In this work, we assume that ea…

cs.CL20165 cited

Evaluating Induced CCG Parsers on Grounded Semantic Parsing

Yonatan Bisk, Siva Reddy, John Blitzer +2

We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic…