150 citations · 152 across the 7 of their papers we have counts for
8 papers · 1 filter
Selectively Answering Ambiguous Questions
Jeremy R. Cole, Michael J. Q. Zhang, Daniel Gillick +3
Trustworthy language models should abstain from answering questions when they do not know the answer. However, the answer to a question can be unknown for a variety of reasons. Pri…
NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders
Livio Baldini Soares, Daniel Gillick, Jeremy R. Cole +1
Neural document rerankers are extremely effective in terms of accuracy. However, the best models require dedicated hardware for serving, which is costly and often not feasible. To…
Salient Span Masking for Temporal Understanding
Jeremy R. Cole, Aditi Chaudhary, Bhuwan Dhingra +1
Salient Span Masking (SSM) has shown itself to be an effective strategy to improve closed-book question answering performance. SSM extends general masked language model pretraining…
DIFFQG: Generating Questions to Summarize Factual Changes
Jeremy R. Cole, Palak Jain, Julian Martin Eisenschlos +3
Identifying the difference between two versions of the same article is useful to update knowledge bases and to understand how articles evolve. Paired texts occur naturally in diver…
Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour
Fangyu Liu, Julian Martin Eisenschlos, Jeremy R. Cole +1
Language models (LMs) trained on raw texts have no direct access to the physical world. Gordon and Van Durme (2013) point out that LMs can thus suffer from reporting bias: texts ra…
WinoDict: Probing language models for in-context word acquisition
Julian Martin Eisenschlos, Jeremy R. Cole, Fangyu Liu +1
We introduce a new in-context learning paradigm to measure Large Language Models' (LLMs) ability to learn novel words during inference. In particular, we rewrite Winograd-style co-…
Graph-Based Decoding for Task Oriented Semantic Parsing
Jeremy R. Cole, Nanjiang Jiang, Panupong Pasupat +2
The dominant paradigm for semantic parsing in recent years is to formulate parsing as a sequence-to-sequence task, generating predictions with auto-regressive sequence decoders. In…
Time-Aware Language Models as Temporal Knowledge Bases
Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos +3
Many facts come with an expiration date, from the name of the President to the basketball team Lebron James plays for. But language models (LMs) are trained on snapshots of data co…