pub.chive.eprint.submission
Samples
210 randomly sampled records from the AT Protocol firehose
pub.chive.eprint.submission (100 samples)
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"content": "In Partial Control, the understood subject of an obligatorily controlled complement is construed as properly containing the controlling argument (e.g., John wanted [PRO to gather at noon], where PRO = John and contextually salient others). Since this phenomenon was first systematically described by Landau (2000), many accounts of it have been offered. But some of the diversity in these accounts reflects disagreement over what the facts are. To address this, we use experimental syntax to collect and analyze sentence acceptability judgments that bear on the availability of Partial Control across a wide range of control predicates. Results indicate a substantial amount of gradability in the availability of Partial Control as a function of the choice of control predicate, in a way that depends in part on the predicate’s temporal, aspectual, and modal properties. Although these findings are not fully consistent with any existing approach to Partial Control, we suggest that Pearson’s (2013) approach lays a promising foundation for further research.",
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"abstractPlainText": "In Partial Control, the understood subject of an obligatorily controlled complement is construed as properly containing the controlling argument (e.g., John wanted [PRO to gather at noon], where PRO = John and contextually salient others). Since this phenomenon was first systematically described by Landau (2000), many accounts of it have been offered. But some of the diversity in these accounts reflects disagreement over what the facts are. To address this, we use experimental syntax to collect and analyze sentence acceptability judgments that bear on the availability of Partial Control across a wide range of control predicates. Results indicate a substantial amount of gradability in the availability of Partial Control as a function of the choice of control predicate, in a way that depends in part on the predicate’s temporal, aspectual, and modal properties. Although these findings are not fully consistent with any existing approach to Partial Control, we suggest that Pearson’s (2013) approach lays a promising foundation for further research.",
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"handle": "aaronstevenwhite.io",
"name": "Aaron Steven White",
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},
{
"name": "Thomas Grano",
"order": 2
}
],
"conferencePresentation": {
"conferenceName": "Proceedings of Sinn und Bedeutung"
},
"createdAt": "2014-01-01T00:00:00.000Z",
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"publishedVersion": {
"journal": "Proceedings of Sinn und Bedeutung",
"pages": "469–486",
"publishedAt": "2014-01-01T00:00:00.000Z",
"volume": "18"
},
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"platformSlug": "other",
"url": "https://github.com/aaronstevenwhite/PartialControlExperiments"
}
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"title": "An experimental investigation of partial control",
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}did:plc:34mbm5v3umztwvvgnttvcz6e | at://did:plc:34mbm5v3umztwvvgnttvcz6e/pub.chive.eprint.submission/3mufmdeoyuo2d
pub.chive.richtext.defs (nested within pub.chive.eprint.submission) (100 samples)
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"content": "We propose to unify a variety of existing semantic classification tasks, such as semantic role labeling, anaphora resolution, and paraphrase detection, under the heading of Recognizing Textual Entailment (RTE). We present a general strategy to automatically generate one or more sentential hypotheses based on an input sentence and pre-existing manual semantic annotations. The resulting suite of datasets enables us to probe a statistical RTE model's performance on different aspects of semantics. We demonstrate the value of this approach by investigating the behavior of a popular neural network RTE model.",
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"abstractPlainText": "We propose to unify a variety of existing semantic classification tasks, such as semantic role labeling, anaphora resolution, and paraphrase detection, under the heading of Recognizing Textual Entailment (RTE). We present a general strategy to automatically generate one or more sentential hypotheses based on an input sentence and pre-existing manual semantic annotations. The resulting suite of datasets enables us to probe a statistical RTE model's performance on different aspects of semantics. We demonstrate the value of this approach by investigating the behavior of a popular neural network RTE model.",
"authors": [
{
"affiliations": [
{
"name": "University of Rochester",
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"did": "did:plc:34mbm5v3umztwvvgnttvcz6e",
"handle": "aaronstevenwhite.io",
"name": "Aaron Steven White",
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{
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"name": "Pushpendre Rastogi",
"order": 2
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{
"affiliations": [
{
"name": "Johns Hopkins University",
"rorId": "https://ror.org/00za53h95"
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],
"name": "Kevin Duh",
"order": 3
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{
"affiliations": [
{
"name": "Johns Hopkins University",
"rorId": "https://ror.org/00za53h95"
}
],
"name": "Benjamin Van Durme",
"order": 4
}
],
"conferencePresentation": {
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"conferenceIteration": "IJCNLP 2017",
"conferenceLocation": "Taipei, Taiwan",
"conferenceName": "International Joint Conference on Natural Language Processing"
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"journal": "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
"pages": "996–1005",
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"publisher": "Asian Federation of Natural Language Processing",
"url": "https://aclanthology.org/I17-1100"
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"title": "Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework",
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}did:plc:34mbm5v3umztwvvgnttvcz6e | at://did:plc:34mbm5v3umztwvvgnttvcz6e/pub.chive.eprint.submission/3mufmcvep5o2t
pub.chive.richtext.facets (nested within pub.chive.eprint.submission) (8 samples)
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"content": "Event-keyed summarization (EKS) requires summarizing a specific event described in a document given the document text and an event representation extracted from it. In this work, we extend EKS to the cross-document setting (CDEKS), in which summaries must synthesize information from accounts of the same event as given by multiple sources. We introduce SEAMuS (Summaries of Events Across Multiple Sources), a high-quality dataset for CDEKS based on an expert reannotation of the FAMuS dataset for cross-document argument extraction. We present a suite of baselines on SEAMuS—covering both smaller, fine-tuned models, as well as zero- and few-shot prompted LLMs—along with detailed ablations and a human evaluation study, showing SEAMuS to be a valuable benchmark for this new task.",
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"authors": [
{
"name": "William Walden",
"order": 1
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{
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{
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"handle": "alexmartin314.bsky.social",
"name": "Alexander Martin",
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{
"name": "Chihsheng Jin",
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{
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{
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"publisher": "Association for Computational Linguistics",
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}did:plc:34mbm5v3umztwvvgnttvcz6e | at://did:plc:34mbm5v3umztwvvgnttvcz6e/pub.chive.eprint.submission/3mufma6ziks2y
pub.chive.richtext.text (nested within pub.chive.eprint.submission) (2 samples)
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"abstract": [
{
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"content": "A throwaway eprint used to verify that records from other atproto services attach to a paper and render on it. Safe to delete.",
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}
],
"authors": [
{
"did": "did:plc:34mbm5v3umztwvvgnttvcz6e",
"name": "Aaron Steven White",
"order": 1
}
],
"createdAt": "2026-09-04T20:46:45.493081Z",
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"url": "https://github.com/chive-pub/chive"
},
{
"label": "Probe repo on Tangled",
"platformSlug": "tangled",
"recordUri": "at://did:plc:34mbm5v3umztwvvgnttvcz6e/sh.tangled.repo/interop-probe"
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"submittedBy": "did:plc:34mbm5v3umztwvvgnttvcz6e",
"title": "[TEST] Interop verification probe — safe to delete"
}did:plc:34mbm5v3umztwvvgnttvcz6e | at://did:plc:34mbm5v3umztwvvgnttvcz6e/pub.chive.eprint.submission/3muptixquo527