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Alexandra Birch

19 papers hereh-index 9225 citations36 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6
  • last author13

Across the 19 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CL18
  • cs.AI1
same name
  • Alexandra Birch — 36 papers, h 32
  • Alexandra Birch — 7 papers, h 6
  • Alexandra Birch — 5 papers, h 4
  • Alexandra Birch — 4 papers, h 2
  • Alexandra Birch — 3 papers, h 2
  • Alexandra Birch — 2 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedMultilingual Retrieval-Augmented Generation for Knowledge-Intensive Task

4 citations · 14 across the 19 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CL2023

Retrieval-augmented Multilingual Knowledge Editing

Weixuan Wang, Barry Haddow, Alexandra Birch

Knowledge represented in Large Language Models (LLMs) is quite often incorrect and can also become obsolete over time. Updating knowledge via fine-tuning is computationally resourc…

cs.CL2023

The Ups and Downs of Large Language Model Inference with Vocabulary Trimming by Language Heuristics

Nikolay Bogoychev, Pinzhen Chen, Barry Haddow +1

Deploying large language models (LLMs) encounters challenges due to intensive computational and memory requirements. Our research examines vocabulary trimming (VT) inspired by rest…

cs.CL2023★ 4 cited

Cache & Distil: Optimising API Calls to Large Language Models

Guillem Ramírez, Matthias Lindemann, Alexandra Birch +1

Large-scale deployment of generative AI tools often depends on costly API calls to a Large Language Model (LLM) to fulfil user queries. To curtail the frequency of these calls, one…

cs.CL2023★ 3 cited

Assessing the Reliability of Large Language Model Knowledge

Weixuan Wang, Barry Haddow, Alexandra Birch +1

Large language models (LLMs) have been treated as knowledge bases due to their strong performance in knowledge probing tasks. LLMs are typically evaluated using accuracy, yet this…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.