docs/faiss/document_lookup.txt

Document 0:
Source: https://julien-ser.github.io/JulienSerbanescu/
Type: Unknown
Content Preview: Julien Serbanescu




Julien Serbanescu...
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Document 1:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: UnAnswGen: A Systematic Approach for Generating
Unanswerable Questions in Machine Reading Comprehens...
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Document 2:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Unlike existing datasets like SQuAD2.0, which do not account for
the reasons behind question unanswe...
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Document 3:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: query reformulation. The resulting UnAnswGen dataset and asso-
ciated software workflow are made pub...
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Document 4:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: on the first page. Copyrights for components of this work owned by others than the
author(s) must be...
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Document 5:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Development in Information Retrieval in the Asia Pacific Region (SIGIR-AP
’24), December 9–12, 2024,...
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Document 6:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: should avoid responding rather than making uncertain guesses,
demonstrating their language comprehen...
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Document 7:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: systems advance to meet the complexity of real-world information
needs, there is an increasing deman...
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Document 8:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: SIGIR-AP ’24, December 9–12, 2024, Tokyo, Japan Hadiseh Moradisani, Fattane Zarrinkalam, Julien Serb...
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Document 9:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: SQuAD2-CR
[17] Wikip
edia Cr
owdsourcing (86,821
- 43,498) 6 [19] 2020
Dur
eader [11] Chinese
search...
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Document 10:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: instance, it contains only 3,350 unanswerable questions labeled
with No Information. Moreover, as th...
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Document 11:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: ing unanswerable questions and enables the exploration of various
causes of unanswerability. The onl...
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Document 12:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: unanswerable questions into answerable ones.
To develop a multi-label MRC dataset with unanswerable ...
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Document 13:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: mation for each input question. Second, the generated candidate
unanswerable questions are evaluated...
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Document 14:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: The advantages of our work are twofold: (1) Our implementation
of the proposed software workflow all...
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Document 15:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: of SQuAD2.0 that includes multi-labeled unanswerable questions.
Figure 1 presents the overview of ou...
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Document 16:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: UnAnswGen: A Systematic Approach for Generating Unanswerable Questions in Machine Reading Comprehens...
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Document 17:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: linguistic dimensions such as entity swap, number swap, negation,
antonym, mutual exclusion, and no ...
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Document 18:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: passage, and its candidate unanswerable questions. We have imple-
mented and integrated a comprehens...
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Document 19:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: placement: For each entity in the input answerable question, we
replace it with another entity of th...
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Document 20:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: corresponding context.
Number Swap. Number Swap involves modifying a question to
potentially render ...
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Document 21:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Time magazine named her one of the most 100 influential people of the
century? could be Time magazin...
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Document 22:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: (2) Replacement: Replace each identified word with its antonym,
ensuring the modified question remai...
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Document 23:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: SIGIR-AP ’24, December 9–12, 2024, Tokyo, Japan Hadiseh Moradisani, Fattane Zarrinkalam, Julien Serb...
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Document 24:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: of her music?, utilizing the Detection and Removal approach might
lead to a question such as Beyoncé...
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Document 25:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: formation available in the given context, the question becomes
inherently unanswerable. For instance...
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Document 26:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: No Information. Similar to [33], to modify the original answer-
able questions by considering this c...
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Document 27:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: California is also home to a large homegrown surf and skateboard cul-
ture.... This method ensures t...
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Document 28:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: 𝑎𝑖 , and for each candidate unanswerable question (𝑐𝑗,𝑙𝑗 ) ∈𝐶𝑞𝑖 , we
conduct the following evaluatio...
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Document 29:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: 𝑞𝑖 , denoted as 𝑞′
𝑖 , to 𝑈𝑞𝑖 , and attribute 𝑙𝑗 as the reason for the
unanswerability of 𝑞′
𝑖 .
The...
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Document 30:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: are answerable. This dataset, developed through crowdsourcing,
consists of a training set with 130,3...
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Document 31:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: swerable candidate questions from a single modification process.
Consequently, from the 86,821 answe...
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Document 32:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: UnAnswGen: A Systematic Approach for Generating Unanswerable Questions in Machine Reading Comprehens...
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Document 33:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: ele
ctra-base-squad2 74.8 84.7 84.7 67.9 87.8 93.5 72.2 81.6 89.9
r
oberta-large-squad 78.7 90 90 69...
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Document 34:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: questions by returning a null or empty string when no appropri-
ate answer is found within the conte...
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Document 35:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: score indicating the model’s certainty in its provided answer. For
unanswerable questions, these mod...
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Document 36:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Table 4: Statistics on UnAnswGen dataset.
Unansw
erability Classes #
of Questions Per
centage A
vera...
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Document 37:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: of the final unanswerable question set. Specifically, questions from
the Negation category account f...
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Document 38:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: under the Negation label, 31.95 unanswerable questions under the
Antonym label, and only 2.6 unanswe...
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Document 39:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: indicates that the question is completely unrelated to the context,
whereas a score of 1 indicates s...
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Document 40:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: SIGIR-AP ’24, December 9–12, 2024, Tokyo, Japan Hadiseh Moradisani, Fattane Zarrinkalam, Julien Serb...
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Document 41:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: SQuAD2-CR+UnAnsw
Gen 71.93 71.93 92.48 96.09 51.43 58.27 46.83 63.78 69.17 81.77 64.86 78.69 86.8 92...
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Document 42:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: to evaluate the UnAnswerGen dataset against these criteria. Table
6 presents the results of Krippend...
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Document 43:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: CR, which already includes multi-class labeling of unanswerable
questions, and (2) the SQuAD2-CR tra...
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Document 44:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: underwent training on both the enhanced SQuAD2.0+ UnAnswGen
and the original SQuAD2-CR datasets, wit...
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Document 45:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: BERTa, and 1% for Electra were observed. The balanced dataset
successfully mitigates issues related ...
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Document 46:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: hanced MRC datasets, with a focus on including multi-label unan-
swerable questions. We have develop...
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Document 47:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: flow to enrich other datasets, such as HotPotQA [35] and Natural
Questions [16], with multi-label un...
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Document 48:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: UnAnswGen: A Systematic Approach for Generating Unanswerable Questions in Machine Reading Comprehens...
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Document 49:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: 3115–3119.
[4] Christopher Clark and Matt Gardner. 2017. Simple and effective multi-paragraph
readin...
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Document 50:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: ciation for Computational Linguistics: EMNLP 2023. 7349–7360.
[9] Kilem L Gwet. 2011. On the Krippen...
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Document 51:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: questions. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 33.
6529–6537.
[13...
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Document 52:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: [16] Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur
Parikh, Chris Alb...
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Document 53:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: 2022. Ptau: Prompt tuning for attributing unanswerable questions. In Proceedings
of the 45th Interna...
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Document 54:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Answer Networks for Machine Reading Comprehension. In Proceedings of the
56th Annual Meeting of the ...
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Document 55:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Majumder, and Li Deng. 2016. Ms marco: A human-generated machine reading
comprehension dataset. (201...
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Document 56:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: Unanswerable questions for SQuAD. arXiv preprint arXiv:1806.03822 (2018).
[30] Pranav Rajpurkar, Jia...
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Document 57:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: 7th CCF International Conference, NLPCC 2018, Hohhot, China, August 26–30, 2018,
Proceedings, Part I...
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Document 58:
Source: docs/pdfs\paper.pdf
Type: Unknown
Content Preview: [36] Changchang Zeng, Shaobo Li, Qin Li, Jie Hu, and Jianjun Hu. 2020. A survey
on machine reading c...
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Document 59:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: Julien Serbanescu
437-260-3435 | [email protected] | linkedin.com/in/julien-serbanescu-6ba52a241 ...
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Document 60:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: Innovation/Creativity, Technical Communication, Mentoring
Education
Computer Engineering Co-op Major...
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Document 61:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: on publications. /external-link-altUtilized various NLP methods such as NLTK and SpaCy in Python to ...
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Document 62:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: application (Windows EXE) for cybersecurity threat detection and testing
Organizations
Guelph AI Clu...
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Document 63:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: • /external-link-altLed a team to develop an AI assistant inspired by Jarvis from Iron Man, ensuring...
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Document 64:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: • Developing robotics software using Docker and Linux, implementing Python-based control for Webots
...
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Document 65:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: codes and provide medicine information, working on backend, delegating frontend and bridging
• /exte...
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Document 66:
Source: docs/pdfs\resume.pdf
Type: Unknown
Content Preview: with a ReactJS frontend dashboard for configuring and managing academic research projects
GAN to Gen...
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Document 67:
Source: BinThere.ai.m4a
Type: audio_transcription
Content Preview: All right, so today we're going to be quickly demoing binthere.ai.  Now, what this does, it will det...
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Document 68:
Source: BinThere.ai.m4a
Type: audio_transcription
Content Preview: list it as biodegradable piece.  So if I lower it down just because it's getting the white backgroun...
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Document 69:
Source: BinThere.ai.m4a
Type: audio_transcription
Content Preview: This is our new max score.  And then as I listed there, and then it says it typically goes in a comp...
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Document 70:
Source: Synthia by Nuvela-AI.m4a
Type: audio_transcription
Content Preview: This is the user interface review of Cynthia,  which is a service that makes research papers smarter...
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Document 71:
Source: Synthia by Nuvela-AI.m4a
Type: audio_transcription
Content Preview: load in certain fragments of other papers  that have relevant pieces of information  to what exactly...
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Document 72:
Source: Synthia by Nuvela-AI.m4a
Type: audio_transcription
Content Preview: machinery reading comprehension  in order to find user sentiment.  Something like that.  And then we...
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Document 73:
Source: Synthia by Nuvela-AI.m4a
Type: audio_transcription
Content Preview: be another tool  that the model context protocol system using  and topic would actually be able to e...
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Document 74:
Source: Synthia by Nuvela-AI.m4a
Type: audio_transcription
Content Preview: to use.  And it helps just make research smarter, more efficient,  and better for users overall.  No...
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Document 75:
Source: Synthia by Nuvela-AI.m4a
Type: audio_transcription
Content Preview: on our existing formatted proxy late-tech code.  So that's my overview for our Cynthia front-end  or...
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