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Found 7 papers, 4 papers with code
Noun-MWP: Math Word Problems Meet Noun Answers
We introduce a new type of problems for math word problem (MWP) solvers, named Noun-MWPs, whose answer is a non-numerical string containing a noun from the problem text.
Broadband Ground Motion Synthesis by Diffusion Model with Minimal Condition
We also design a domain-specific training method that exploits the traits of earthquake dataset: multiple observed waveforms time-aligned and paired to each earthquake source that are tagged with seismological metadata comprised of earthquake magnitude, depth of focus, and the locations of epicenter and seismometers.
ABC3: Active Bayesian Causal Inference with Cohn Criteria in Randomized Experiments
In causal inference, randomized experiment is a de facto method to overcome various theoretical issues in observational study.
Pre-trained Language Models Return Distinguishable Probability Distributions to Unfaithfully Hallucinated Texts
In this work, we show the pre-trained language models return distinguishable generation probability and uncertainty distribution to unfaithfully hallucinated texts, regardless of their size and structure.
P5: Plug-and-Play Persona Prompting for Personalized Response Selection
Our system can function as a standard open-domain chatbot if persona information is not available.
Ranked #1 on
Conversational Response Selection
on Persona-Chat
(R20@1 metric)
Virchow: A Million-Slide Digital Pathology Foundation Model
The use of artificial intelligence to enable precision medicine and decision support systems through the analysis of pathology images has the potential to revolutionize the diagnosis and treatment of cancer.
Ranked #1 on
Breast Tumour Classification
on PCam
(Accuracy metric, using extra
training data)
Generative Scene Graph Networks
We formulate GSGN as a variational autoencoder in which the latent representation is a tree-structured probabilistic scene graph.
