A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Filters
Controlling Hallucinations at Word Level in Data-to-Text Generation
[article]
2021
arXiv
pre-print
Preserved Fulltext
Other Versions
Data-to-Text Generation (DTG) is a subfield of Natural Language Generation aiming at transcribing structured data in natural language descriptions. ...
Our model is able to reduce and control hallucinations, while keeping fluency and coherence in generated texts. ...
Keywords Data-to-Text Generation · Hallucinations · Controlled Text Generation
Introduction Data-to-Text Generation (DTG) is the subfield of Computational Linguistics and Natural Language Generation ...
arXiv:2102.02810v2
fatcat:waiacytsubczvfqaesqlzpaglu
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Existing work usually attempts to detect these hallucinations based on a corresponding oracle reference at a sentence or document level. ...
However ground-truth references may not be readily available for many free-form text generation applications, and sentence- or document-level detection may fail to provide the fine-grained signals that ...
Acknowledgments The authors would like to thank the anonymous reviewers for their thoughtful and constructive comments. ...
arXiv:2104.08704v2
fatcat:ozw6ioh32zhh3mmlu32s7vwxoy
Detecting Hallucinated Content in Conditional Neural Sequence Generation
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Codes and data available at https://github.com/violet-zct/fairseq-detect-hallucination. ...
We also apply our method to word-level quality estimation for MT and show its effectiveness in both supervised and unsupervised settings. ...
Acknowledgements The work in this paper was supported in part by a Facebook SRA Award. We thank the anonymous reviewers for the insightful feedback that helps us improve the paper. ...
arXiv:2011.02593v3
fatcat:p4ldz52bhvgqnn2fpfntgqop5u
Survey of Hallucination in Natural Language Generation
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
This advancement has led to more fluent and coherent NLG, leading to improved development in downstream tasks such as abstractive summarization, dialogue generation and data-to-text generation. ...
downstream tasks, namely abstractive summarization, dialogue generation, generative question answering, data-to-text generation, and machine translation. ...
Current works treat the hallucination level as a controllable attribute in order to remains the hallucination in outputs at a low level. ...
arXiv:2202.03629v4
fatcat:s6c26a7orncrffis55q5swo5ue
Hallucinated n-best lists for discriminative language modeling
2012
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
This paper investigates semi-supervised methods for discriminative language modeling, whereby n-best lists are "hallucinated" for given reference text and are then used for training n-gram language models ...
We perform controlled experiments on a very strong baseline English CTS system, comparing three methods for simulating ASR output, and compare the results with training with "real" n-best list output from ...
Machine translation methods Above we discussed methods for generating hallucinated ASR nbest lists using phone-based finite-state transducers. We now turn to generating confusions at the word level. ...
doi:10.1109/icassp.2012.6289043
dblp:conf/icassp/SagaeLPXGKKRSSBCCHHKLPR12
fatcat:emi5pcwldrgdrlvi26wtyh6aqy
Text Generation with Text-Editing Models
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In contrast, seq2seq models generate outputs word-by-word from scratch thus making them slow at inference time. ...
We discuss challenges related to productionization and how these models can be used to mitigate hallucination and bias, both pressing challenges in the field of text generation. ...
These advantages have generated a substantial and continued level of interest in text-editing research. ...
arXiv:2206.07043v1
fatcat:erjlc3paandfjn4w33kibfqgze
Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Neural text generation (data- or text-to-text) demonstrates remarkable performance when training data is abundant which for many applications is not the case. ...
Our contribution is a simple but powerful technique to treat such hallucinations as a controllable aspect of the generated text, without dismissing any input and without modifying the model architecture ...
Word Overlap When the source and the target are similar on the token level, one can use word overlap between them to estimate how many words unsupported by the source are present in the target. ...
arXiv:2010.05873v1
fatcat:xarkkuubkvelbjejy46kakvwei
Learning to Revise References for Faithful Summarization
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
At inference, we vary style codes to over-generate revisions of unsupported reference sentences and select a final revision which balances faithfulness and abstraction. ...
In many real-world scenarios with naturally occurring datasets, reference summaries are noisy and contain information that cannot be inferred from the source text. ...
On a highly noisy dataset of concept-to-text generation (Lebret et al., 2016) , Filippova retains all data and addresses quality by treating hallucinations as a controllable aspect of the generated text ...
arXiv:2204.10290v1
fatcat:ijpetqjua5cyrol2ps3kt4q3xq
Believing is seeing in schizophrenia: The role of top-down processing
2005
Behavioral and Brain Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is application/pdf.
59 words Main Text: 982 words References: 359 words Total Text: 1524 words Abstract: ...
Acknowledgments Supported in part by NARSAD Grable Investigator Award to Sohee Park. ...
Namely, the role of perceptual deficits in RCVH is to simply increase the noise, whereas the actual generation of RCVH lies within faulty higher-level processes. ...
doi:10.1017/s0140525x05400138
fatcat:wpncsvvuknanper7avbdz5mj4m
Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
abstractive summarization, dialogue generation, machine translation, and data-to-text generation. ...
This advancement has resulted in more fluent, coherent and even properties controllable (e.g. stylistic, sentiment, length etc.) generation, naturally leading to development in downstream tasks such as ...
Faithfulness in Data-to-Text Generation Data-to-text generation (or table-to-text generation) has been widely studied for decades. ...
arXiv:2203.05227v1
fatcat:q2u3ojyi6vb7pjt6ajwbinjmpa
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
In open domain table-to-text generation, we notice that the unfaithful generation usually contains hallucinated content which can not be aligned to any input table record. ...
We thus try to evaluate the generation faithfulness with two entity-centric metrics: table record coverage and the ratio of hallucinated entities in text, both of which are shown to have strong agreement ...
Acknowledgments We would like to thank the anonymous reviewers for the helpful discussions and suggestions. ...
arXiv:2102.08585v1
fatcat:5ofv2kustfdg3dqzjy7ufpjfne
ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Further, we apply data augmentation in conjunction with meta-learning to reduce sampling bias. ...
We make use of a conditional generator for data augmentation that is trained directly using the meta-learning objective and simultaneously with prototypical networks, hence ensuring that data augmentation ...
The encoder takes in a combination of character-level and word-level representations at the input. Character representations are learnt using a 2-D convolution neural network. ...
arXiv:2101.11753v1
fatcat:fmyl7vidyrdutlo2uumbhebjsq
A Neural Network Simulation of Hallucinated "Voices" and Associated Speech Perception Impairments in Schizophrenic Patients
1995
Journal of Cognitive Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Pruning anatomic connections or reducing neuronal activation in working memory caused word "percepts" t o emerge spontaneously (i.e., in the absence of external "speech inputs"), thereby providing a model ...
of hallucinated speech. ...
The fact that the model could not be manipulated to fit performance data for all individual hallucinators predicts that factors other than pruning level and bias were at work, but that these factors, in ...
doi:10.1162/jocn.1995.7.4.479
pmid:23961906
fatcat:6cfinfgwezbe7o4af6hqphynle
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
State-of-the-art abstractive summarization systems often generate hallucinations; i.e., content that is not directly inferable from the source text. ...
These factual hallucinations can be beneficial in a summary by providing useful background information. ...
Filippova (2020) proposed a method for controlling hallucination in data-to-text generation task. ...
arXiv:2109.09784v2
fatcat:xeowmhalbnebpfdlvop64sezce
A Simple Recipe towards Reducing Hallucination in Neural Surface Realisation
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
at Microsoft. ...
To mitigate this issue, we propose to integrate a language understanding module for data refinement with selftraining iterations to effectively induce strong equivalence between the input data and the ...
The contact author of this paper, according to the meaning given to this role by Sun Yat-Sen University, is Rong Pan. ...
doi:10.18653/v1/p19-1256
dblp:conf/acl/NieYWPL19
fatcat:jed4iroe2nfadpc6igvfmesglm
« Previous
Showing results 1 — 15 out of 9,376 results