Search Results for author:
Found 13 papers, 7 papers with code
Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based Results
Recent transformer-based approaches demonstrate promising results on relational scientific information extraction.
Towards a Multi-Entity Aspect-Based Sentiment Analysis for Characterizing Directed Social Regard in Online Messaging
Online messaging is dynamic, influential, and highly contextual, and a single post may contain contrasting sentiments towards multiple entities, such as dehumanizing one actor while empathizing with another in the same message. These complexities are important to capture for understanding the systematic abuse voiced within an online community, or for determining whether individuals are advocating for abuse, opposing abuse, or simply reporting abuse.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
Scalable Data Ablation Approximations for Language Models through Modular Training and Merging
Training data compositions for Large Language Models (LLMs) can significantly affect their downstream performance.
OLMo: Accelerating the Science of Language Models
Given the importance of these details in scientifically studying these models, including their biases and potential risks, we believe it is essential for the research community to have access to powerful, truly open LMs.
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
As a result, it is challenging to conduct and advance scientific research on language modeling, such as understanding how training data impacts model capabilities and limitations.
Paloma: A Benchmark for Evaluating Language Model Fit
We invite submissions to our benchmark and organize results by comparability based on compliance with guidelines such as removal of benchmark contamination from pretraining.
Catwalk: A Unified Language Model Evaluation Framework for Many Datasets
The success of large language models has shifted the evaluation paradigms in natural language processing (NLP).
What's In My Big Data?
We open-source WIMBD's code and artifacts to provide a standard set of evaluations for new text-based corpora and to encourage more analyses and transparency around them.
Reproducibility in NLP: What Have We Learned from the Checklist?
Scientific progress in NLP rests on the reproducibility of researchers' claims.
Just-DREAM-about-it: Figurative Language Understanding with DREAM-FLUTE
We hypothesize that to perform this task well, the reader needs to mentally elaborate the scene being described to identify a sensible meaning of the language.
Exploring The Landscape of Distributional Robustness for Question Answering Models
We conduct a large empirical evaluation to investigate the landscape of distributional robustness in question answering.
From Unstructured Text to Causal Knowledge Graphs: A Transformer-Based Approach
Qualitative causal relationships compactly express the direction, dependency, temporal constraints, and monotonicity constraints of discrete or continuous interactions in the world.
Invertible Frowns: Video-to-Video Facial Emotion Translation
Nevertheless, we demonstrate (1) that facial expressions of emotion can be modified with nothing other than L1 reconstruction and pre-trained emotion objectives and (2) that our automated emotion evaluation approach aligns with human judgements.
