Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Xu, Hainiu"'
Autor:
Li, Jiazheng, Xu, Hainiu, Sun, Zhaoyue, Zhou, Yuxiang, West, David, Aloisi, Cesare, He, Yulan
Generating rationales that justify scoring decisions has been a promising way to facilitate explainability in automated scoring systems. However, existing methods do not match the accuracy of classifier-based methods. Plus, the generated rationales o
Externí odkaz:
http://arxiv.org/abs/2406.19949
Autor:
Dugan, Liam, Hwang, Alyssa, Trhlik, Filip, Ludan, Josh Magnus, Zhu, Andrew, Xu, Hainiu, Ippolito, Daphne, Callison-Burch, Chris
Many commercial and open-source models claim to detect machine-generated text with extremely high accuracy (99% or more). However, very few of these detectors are evaluated on shared benchmark datasets and even when they are, the datasets used for ev
Externí odkaz:
http://arxiv.org/abs/2405.07940
Task embedding, a meta-learning technique that captures task-specific information, has gained popularity, especially in areas such as multi-task learning, model editing, and interpretability. However, it faces challenges with the emergence of prompt-
Externí odkaz:
http://arxiv.org/abs/2402.14522
Existing datasets for narrative understanding often fail to represent the complexity and uncertainty of relationships in real-life social scenarios. To address this gap, we introduce a new benchmark, Conan, designed for extracting and analysing intri
Externí odkaz:
http://arxiv.org/abs/2402.11051
Neural Theory-of-Mind (N-ToM), machine's ability to understand and keep track of the mental states of others, is pivotal in developing socially intelligent agents. However, prevalent N-ToM benchmarks have several shortcomings, including the presence
Externí odkaz:
http://arxiv.org/abs/2402.06044
Much text describes a changing world (e.g., procedures, stories, newswires), and understanding them requires tracking how entities change. An earlier dataset, OpenPI, provided crowdsourced annotations of entity state changes in text. However, a major
Externí odkaz:
http://arxiv.org/abs/2305.14603
Recent work has shown that prompting language models with code-like representations of natural language leads to performance improvements on structured reasoning tasks. However, such tasks comprise only a small subset of all natural language tasks. I
Externí odkaz:
http://arxiv.org/abs/2304.13250
Autor:
Zhang, Tianyi, Tham, Isaac, Hou, Zhaoyi, Ren, Jiaxuan, Zhou, Liyang, Xu, Hainiu, Zhang, Li, Martin, Lara J., Dror, Rotem, Li, Sha, Ji, Heng, Palmer, Martha, Brown, Susan, Suchocki, Reece, Callison-Burch, Chris
Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction(IE), often with limited human curation. We demonstrate a human-in-
Externí odkaz:
http://arxiv.org/abs/2302.13048
Autor:
Zhang, Li, Xu, Hainiu, Yang, Yue, Zhou, Shuyan, You, Weiqiu, Arora, Manni, Callison-Burch, Chris
Entities and events are crucial to natural language reasoning and common in procedural texts. Existing work has focused either exclusively on entity state tracking (e.g., whether a pan is hot) or on event reasoning (e.g., whether one would burn thems
Externí odkaz:
http://arxiv.org/abs/2301.10896