EMNLP
Collection
Accepted papers for EMNLP (Conference on Empirical Methods in Natural Language Processing), one dataset per year. • 13 items • Updated
title stringlengths 18 149 | paper_url stringlengths 43 46 | authors listlengths 1 27 | abstract large_stringlengths 501 2.03k | anthology_id stringlengths 17 20 | doi stringlengths 29 32 ⌀ | award stringclasses 0
values | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values | embedding listlengths 768 768 |
|---|---|---|---|---|---|---|---|---|---|
IAG: Induction-Augmented Generation Framework for Answering Reasoning Questions | https://aclanthology.org/2023.emnlp-main.1/ | [
"Zhebin Zhang",
"Xinyu Zhang",
"Yuanhang Ren",
"Saijiang Shi",
"Meng Han",
"Yongkang Wu",
"Ruofei Lai",
"Zhao Cao"
] | Retrieval-Augmented Generation (RAG), by incorporating external knowledge with parametric memory of language models, has become the state-of-the-art architecture for open-domain QA tasks. However, common knowledge bases are inherently constrained by limited coverage and noisy information, making retrieval-based approac... | 2023.emnlp-main.1 | 10.18653/v1/2023.emnlp-main.1 | null | 2311.18397 | title_snapshot | [
0.004589198622852564,
-0.033590126782655716,
0.014802935533225536,
0.06462426483631134,
0.022114360705018044,
0.004598233848810196,
0.03706778585910797,
-0.01356531586498022,
-0.03484426811337471,
0.007412577513605356,
-0.023812975734472275,
0.03250521048903465,
-0.06289821118116379,
-0.00... |
Absolute Position Embedding Learns Sinusoid-like Waves for Attention Based on Relative Position | https://aclanthology.org/2023.emnlp-main.2/ | [
"Yuji Yamamoto",
"Takuya Matsuzaki"
] | Attention weight is a clue to interpret how a Transformer-based model makes an inference. In some attention heads, the attention focuses on the neighbors of each token. This allows the output vector of each token to depend on the surrounding tokens and contributes to make the inference context-dependent. We analyze the... | 2023.emnlp-main.2 | 10.18653/v1/2023.emnlp-main.2 | null | null | null | [
-0.018956895917654037,
-0.0024844591971486807,
0.0298289954662323,
0.015897236764431,
0.006025917362421751,
0.012649184092879295,
0.028859447687864304,
0.03731956332921982,
-0.047994691878557205,
-0.021575063467025757,
-0.030036374926567078,
0.010516985319554806,
-0.04903843626379967,
-0.0... |
Chinese Lexical Substitution: Dataset and Method | https://aclanthology.org/2023.emnlp-main.3/ | [
"Jipeng Qiang",
"Kang Liu",
"Ying Li",
"Yun Li",
"Yi Zhu",
"Yun-Hao Yuan",
"Xiaocheng Hu",
"Xiaoye Ouyang"
] | Existing lexical substitution (LS) benchmarks were collected by asking human annotators to think of substitutes from memory, resulting in benchmarks with limited coverage and relatively small scales. To overcome this problem, we propose a novel annotation method to construct an LS dataset based on human and machine col... | 2023.emnlp-main.3 | 10.18653/v1/2023.emnlp-main.3 | null | null | null | [
-0.025031426921486855,
-0.02118723653256893,
-0.05046769976615906,
0.04012412205338478,
0.0705689787864685,
0.03494945913553238,
-0.0010435988660901785,
0.030168067663908005,
0.00504343444481492,
-0.01914534904062748,
-0.044432103633880615,
0.021737150847911835,
-0.04873041808605194,
-0.03... |
Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecasting | https://aclanthology.org/2023.emnlp-main.4/ | [
"Chenkai Sun",
"Jinning Li",
"Yi Fung",
"Hou Chan",
"Tarek Abdelzaher",
"ChengXiang Zhai",
"Heng Ji"
] | Automatic response forecasting for news media plays a crucial role in enabling content producers to efficiently predict the impact of news releases and prevent unexpected negative outcomes such as social conflict and moral injury. To effectively forecast responses, it is essential to develop measures that leverage the ... | 2023.emnlp-main.4 | 10.18653/v1/2023.emnlp-main.4 | null | 2310.13297 | title_snapshot | [
0.038290686905384064,
-0.05255293473601341,
-0.0014905148418620229,
0.031757600605487823,
0.016639474779367447,
0.035052817314863205,
0.06063501536846161,
0.010587832890450954,
-0.04123338684439659,
-0.026157453656196594,
-0.020813774317502975,
0.006776377093046904,
-0.060986436903476715,
... |
Fine-grained Conversational Decoding via Isotropic and Proximal Search | https://aclanthology.org/2023.emnlp-main.5/ | [
"Yuxuan Yao",
"Han Wu",
"Qiling Xu",
"Linqi Song"
] | General-purpose text decoding approaches are usually adopted for dialogue response generation. Although the quality of the generated responses can be improved with dialogue-specific encoding methods, conversational decoding methods are still under-explored. Inspired by SimDRC that a good dialogue feature space should f... | 2023.emnlp-main.5 | 10.18653/v1/2023.emnlp-main.5 | null | 2310.08130 | title_snapshot | [
-0.020372088998556137,
-0.007624293211847544,
-0.00015217959298752248,
0.080552838742733,
0.04515308886766434,
0.05985689163208008,
0.03396783024072647,
0.005898779723793268,
0.006176250521093607,
-0.0480772890150547,
-0.011823010630905628,
0.0006499748560599983,
-0.05766742676496506,
-0.0... |
Holistic Inter-Annotator Agreement and Corpus Coherence Estimation in a Large-scale Multilingual Annotation Campaign | https://aclanthology.org/2023.emnlp-main.6/ | [
"Nicolas Stefanovitch",
"Jakub Piskorski"
] | In this paper we report on the complexity of persuasion technique annotation in the context of a large multilingual annotation campaign involving 6 languages and approximately 40 annotators. We highlight the techniques that appear to be difficult for humans to annotate and elaborate on our findings on the causes of thi... | 2023.emnlp-main.6 | 10.18653/v1/2023.emnlp-main.6 | null | null | null | [
-0.02076372504234314,
-0.01415550522506237,
-0.004803049378097057,
0.023556100204586983,
0.004063941538333893,
0.007821411825716496,
0.02959008701145649,
0.007519172970205545,
-0.010593184269964695,
-0.004718909040093422,
-0.026354268193244934,
0.030768180266022682,
-0.05754414573311806,
-... |
PHD: Pixel-Based Language Modeling of Historical Documents | https://aclanthology.org/2023.emnlp-main.7/ | [
"Nadav Borenstein",
"Phillip Rust",
"Desmond Elliott",
"Isabelle Augenstein"
] | The digitisation of historical documents has provided historians with unprecedented research opportunities. Yet, the conventional approach to analysing historical documents involves converting them from images to text using OCR, a process that overlooks the potential benefits of treating them as images and introduces h... | 2023.emnlp-main.7 | 10.18653/v1/2023.emnlp-main.7 | null | 2310.18343 | title_snapshot | [
-0.03227197378873825,
0.004565990064293146,
-0.030407382175326347,
0.04825659096240997,
0.04352201521396637,
0.05068693682551384,
0.03507472574710846,
0.04569493234157562,
-0.028860773891210556,
-0.02111770026385784,
-0.03520374745130539,
-0.018220366910099983,
-0.04369881749153137,
0.0179... |
Primacy Effect of ChatGPT | https://aclanthology.org/2023.emnlp-main.8/ | [
"Yiwei Wang",
"Yujun Cai",
"Muhao Chen",
"Yuxuan Liang",
"Bryan Hooi"
] | Instruction-tuned large language models (LLMs), such as ChatGPT, have led to promising zero-shot performance in discriminative natural language understanding (NLU) tasks. This involves querying the LLM using a prompt containing the question, and the candidate labels to choose from. The question-answering capabilities o... | 2023.emnlp-main.8 | 10.18653/v1/2023.emnlp-main.8 | null | 2310.13206 | title_snapshot | [
-0.02965172380208969,
-0.022807611152529716,
-0.026555225253105164,
0.05670608580112457,
0.0439998023211956,
-0.0025845360942184925,
0.03706548735499382,
0.052762240171432495,
-0.02754579298198223,
0.0025273531209677458,
-0.041447848081588745,
0.050304677337408066,
-0.055839184671640396,
-... |
Evaluating the Rationale Understanding of Critical Reasoning in Logical Reading Comprehension | https://aclanthology.org/2023.emnlp-main.9/ | [
"Akira Kawabata",
"Saku Sugawara"
] | To precisely evaluate a language model’s capability for logical reading comprehension, we present a dataset for testing the understanding of the rationale behind critical reasoning. For questions taken from an existing multiple-choice logical reading comprehension dataset, we crowdsource rationale texts that explain wh... | 2023.emnlp-main.9 | 10.18653/v1/2023.emnlp-main.9 | null | 2311.18353 | title_snapshot | [
-0.019877798855304718,
-0.009210241958498955,
-0.038852062076330185,
0.05605916306376457,
0.07063666731119156,
-0.0008034958736971021,
0.02592730149626732,
0.039825696498155594,
-0.020735684782266617,
0.030238978564739227,
-0.010284505784511566,
0.05886252224445343,
-0.04081915691494942,
-... |
Evaluating and Modeling Attribution for Cross-Lingual Question Answering | https://aclanthology.org/2023.emnlp-main.10/ | [
"Benjamin Muller",
"John Wieting",
"Jonathan H. Clark",
"Tom Kwiatkowski",
"Sebastian Ruder",
"Livio Baldini Soares",
"Roee Aharoni",
"Jonathan Herzig",
"Xinyi Wang"
] | Trustworthy answer content is abundant in many high-resource languages and is instantly accessible through question answering systems — yet this content can be hard to access for those that do not speak these languages. The leap forward in cross-lingual modeling quality offered by generative language models offers much... | 2023.emnlp-main.10 | 10.18653/v1/2023.emnlp-main.10 | null | 2305.14332 | title_snapshot | [
-0.0003854126844089478,
-0.005824886728078127,
-0.01235975418239832,
0.09536844491958618,
0.016911301761865616,
0.005439496599137783,
0.011700849048793316,
0.02622322365641594,
-0.0015082458266988397,
-0.00561477430164814,
-0.05398525297641754,
0.04930128529667854,
-0.059337127953767776,
-... |
Better Quality Pre-training Data and T5 Models for African Languages | https://aclanthology.org/2023.emnlp-main.11/ | [
"Akintunde Oladipo",
"Mofetoluwa Adeyemi",
"Orevaoghene Ahia",
"Abraham Toluwalase Owodunni",
"Odunayo Ogundepo",
"David Ifeoluwa Adelani",
"Jimmy Lin"
] | In this study, we highlight the importance of enhancing the quality of pretraining data in multilingual language models. Existing web crawls have demonstrated quality issues, particularly in the context of low-resource languages. Consequently, we introduce a new multilingual pretraining corpus for 16 African languages,... | 2023.emnlp-main.11 | 10.18653/v1/2023.emnlp-main.11 | null | null | null | [
-0.019917620345950127,
-0.03704741224646568,
-0.0016665990697219968,
0.058733757585287094,
0.052138593047857285,
0.028183411806821823,
0.03494381532073021,
0.015092611312866211,
-0.029189901426434517,
-0.02112683281302452,
-0.043396126478910446,
0.04986492171883583,
-0.05899294093251228,
0... |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 26