activity
20222024
most citedDr.ICL: Demonstration-Retrieved In-context Learning

7 citations · 22 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CL20246 cited

In-context Learning with Retrieved Demonstrations for Language Models: A Survey

Man Luo, Xin Xu, Yue Liu +2

Language models, especially pre-trained large language models, have showcased remarkable abilities as few-shot in-context learners (ICL), adept at adapting to new tasks with just a…

cs.CL20231 cited

MDDial: A Multi-turn Differential Diagnosis Dialogue Dataset with Reliability Evaluation

Srija Macherla, Man Luo, Mihir Parmar +1

Dialogue systems for Automatic Differential Diagnosis (ADD) have a wide range of real-life applications. These dialogue systems are promising for providing easy access and reducing…

cs.CL20237 cited

Dr.ICL: Demonstration-Retrieved In-context Learning

Man Luo, Xin Xu, Zhuyun Dai +5

In-context learning (ICL), teaching a large language model (LLM) to perform a task with few-shot demonstrations rather than adjusting the model parameters, has emerged as a strong…

cs.CL20231 cited

Can NLP Models Correctly Reason Over Contexts that Break the Common Assumptions?

Neeraj Varshney, Mihir Parmar, Nisarg Patel +4

Pre-training on large corpora of text enables the language models to acquire a vast amount of factual and commonsense knowledge which allows them to achieve remarkable performance…

cs.CL20223 cited

BioTABQA: Instruction Learning for Biomedical Table Question Answering

Man Luo, Sharad Saxena, Swaroop Mishra +2

Table Question Answering (TQA) is an important but under-explored task. Most of the existing QA datasets are in unstructured text format and only few of them use tables as the cont…