Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
Paper • 2407.00066 • Published
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Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"F-score Kappa"
] | task460-a75850e6200b48c8ac9809e3f1c27c5d |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"LR + Bag-of-words Tweet2vec LR + All Features (tweet-level) LR + All Features (chunk-level) FacTweet (tweet-level) Top-$k$ replies, likes, or re-tweets"
] | task460-d091f9ddd4c34d9b9203693db598cbd7 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Karpathy and Fei-Fei's split for MS-COCO dataset BIBREF10"
] | task460-ab3d5637d30e48aa84d3c8995facc682 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"eight layers"
] | task460-02ddcc889f0d42018f30202cd73665c7 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Direct comparison of model parameters"
] | task460-b302b995d1d340508c833d7cbad6ef84 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"simplified set of input data, in a variety of different formats that occur frequently in a healthcare setting"
] | task460-de52c26197a54125acc2dce57a5d9c47 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"16 different datasets from several popular review corpora used in BIBREF20 CoNLL 2000 BIBREF22"
] | task460-9aaaab40989949bba0557e4f9ce92d7e |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"merging, concatenating, or averaging the entity and its features to compute its embeddings graph embedding approaches matrix factorization to jointly embed KB and textual relations"
] | task460-ad5a184f15a54d509040eddca9cf8af4 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Northeast U.S, South U.S., West U.S. and Midwest U.S."
] | task460-f256a39e3e5e4af99ada4a181b1f2373 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"a simulated binning task in which the robot is tasked to place a cube into a bowl as outlined by the verbal command"
] | task460-de07077716e644038b4d675c07e65444 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Word embeddings trained on GoogleNews and Word embeddings trained on Reddit dataset"
] | task460-f22537301a174accadd3575199aa16ef |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"a type of reasoning based on word replacement, requires the ability to capture the interaction between lexical and syntactic structures"
] | task460-4a35f1936b324018a021790484427775 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"No"
] | task460-89ea33bdb22042d9b82ca2ef4580100b |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"English to French and English to German"
] | task460-7e75be91099f4e688d941f4018dda76e |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"the number of distinct word recognition outputs that an attacker can induce"
] | task460-fed4147ae25541cda52f372791ebb5f5 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"The authors showed few tweets where neither and implicit hatred content exist but the model was able to discriminate"
] | task460-7d8c977f0d5b43999f6ec88822d3a15f |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"IMDb dataset of movie reviews"
] | task460-ca51ad0521d94787b33ed10aef351d31 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"By computing number of unique responses and number of responses divided by the number of unique responses to that question for each of the questions"
] | task460-b92e4b1ca04c4c2fa53ba523a5df9a63 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Soft attention Hard Stochastic attention Local Attention"
] | task460-f211a7e45c4a4f9c8a6e754470c901cb |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
" We first encode text inputs using bidirectional LSTMs, then compute summaries using self-attention and conditional summaries using attention. We concatenate text summaries into text features, which, along with visual features, are processed through consecutive layers. In this case of a textual environment, we con... | task460-37de6dc188694514b14bfe3ba582752e |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Private dashboard is leaderboard where competitors can see results after competition is finished - on hidden part of test set (private test set)."
] | task460-3618c1fef18548eb8c79bc904a90df02 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Answer with content missing: (formulas in selection): Pseudo-perplexity is perplexity where conditional joint probability is approximated."
] | task460-a1027f9f6c494dda959157dab0404013 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Yes"
] | task460-07f59a38e1e14d4eb3cc52c3448c3cf3 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"CoNLL-YAGO TAC2010 ACE2004 AQUAINT WW"
] | task460-fed72f1c79f14d79b5960291df2011a7 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"accuracy and F1-score of 89.6% and 89.2%, respectively"
] | task460-737f6fc997e540bf95127bb4f930d368 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"30,000"
] | task460-4b1f98fcfdce4b04955816ddb25e07da |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"$ f_r(h, t) & = & \\Vert \\textbf {W}_{r,1}\\textbf {h} + \\textbf {r} - \\textbf {W}_{r,2}\\textbf {t}\\Vert _{\\ell _{1/2}} $"
] | task460-3d2cdda392ad4e2d8f96620ea6e45477 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"selection of word vectors"
] | task460-f6f56436ed274925b70d84ecc26310eb |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"WN18, FB15k"
] | task460-0daf998942d644bbb62833e03f0f0f82 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"CNN, TIME, 20 Newsgroups, and Reuters-21578"
] | task460-d32bad7dcc4e4bac90826eceee740bd9 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Yes"
] | task460-c6c962cb5ec94ecaac30c591b0e47fe9 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"if it includes negative utterances, negative generalizations and insults concerning ethnicity, nationality, religion and culture."
] | task460-681a771bb5294d6fa026833d4f4dcedd |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"MH17 Twitter dataset"
] | task460-033b8670ae954044a96a63f5be97456b |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Naïve Bayes (NB) Logistic Regression (LR) Support Vector Machine (SVM) Random Forests (RF) Gradient Boosted Trees (GBT) Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN)"
] | task460-ba6e97ccbe3b4988a3545ed16ee875c9 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Annotations from experts are used if they have already been collected."
] | task460-2356c5f85cb64f96aa05b0b134be3031 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"They use a slightly modified copy of the target to create the pseudo-text instead of full BT to make their technique cheaper"
] | task460-7b7d0d4538ff4b8784596c7858fdec78 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"correct classification rate (CCR)"
] | task460-5d991b2fd42a4741989809c82e2bf3ec |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"No"
] | task460-0d8f112324c044cb88182285501d82e6 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"SPARQL"
] | task460-cf2659b0437746cba9e8b0150fb827e4 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"mean reciprocal rank"
] | task460-5d38e8353e5e4c96989c48873aefc3a0 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"a simple word-level encoder The encoder is essentially the same as tweet2vec, with the input as words instead of characters."
] | task460-6b3f9ae5108948b4a0a7f1166dc605e3 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"doc2vec CNN DAN Tree-LSTM DRNN LSTMN C-LSTM SPGK WMD S-WMD Semantic-CNN LSTM-GRNN HN-ATT"
] | task460-11217343bb034d978912580b2685a1cd |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"They randomly sample sentences from Wikipedia that contains an object RC and add them to training data"
] | task460-be3b9c83756e4c8ea63fb68800c98bcb |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"German Spanish Chinese"
] | task460-7950909759854e86a72daad46aab8746 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"same baseline as used by lang2011unsupervised"
] | task460-bf1a3873f18941cb91167a65fec91c85 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"draw our data from news publications, wine reviews, and Reddit develop new metrics for the agreement of binomial orderings across communities and the movement of binomial orderings over time develop a null model to determine how much variation in binomial orderings we might expect across communities and across ti... | task460-55e9d0fb758c4b24bcf11561bf4dda25 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Yes"
] | task460-71c35daa82a6412a8de4116f85621f19 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"trained using Nematus default configuration"
] | task460-652c08d8b02e4c7194e4fae26d6293a1 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"TransE"
] | task460-d2868db8b899479a9639b7b608312174 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"daily Kawish and Awami Awaz Sindhi newspapers Wikipedia dumps short stories and sports news from Wichaar social blog news from Focus Word press blog historical writings, novels, stories, books from Sindh Salamat literary website novels, history and religious books from Sindhi Adabi Board tweets regarding news and... | task460-b6e207fae58f41c391c58b357cc6313c |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"all three representations are concatenated and passed into a MLP"
] | task460-7d3d57bc82c74a76ad02919acd7f809f |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"neural question-answering technique to extract relations from a story text OpenIE5, a commonly used rule-based information extraction technique"
] | task460-ce36075ae34d4a14a4f78e58fd5dfb0b |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"14"
] | task460-d6138ca58f6c454393d2ad8817910bf1 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Yes"
] | task460-6fdc8125fdaa4583b4e092fafe2c4f24 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"53 documents"
] | task460-6c332eabe2c943ed8127d4539dd684d7 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"attention probes using visualizations of the activations created by different pieces of text"
] | task460-d15210f6f0744367879bbb0e03915fd5 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Text Overlap Metrics, including BLEU Perplexity Parameterized Metrics"
] | task460-35b3dc4219294a66b7ecaff6b092e685 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
" inclusion of longer parts of the conversation"
] | task460-10a651c9974a4bc2bb5ad01d081cf9d0 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"rank-correlation BIBREF25"
] | task460-35cdf05ea5a44aeabf63d24d644e92cc |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"BIBREF3 BIBREF4 BIBREF9"
] | task460-95ef61f3b6e142a9a2f98a8165f9d107 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"constructively by selecting the parameters of the multi-head self-attention layer so that the latter acts like a convolutional layer"
] | task460-ed8b77a778974842a39480d37486a4ae |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Informative are those that will not be suppressed by regularization performed."
] | task460-a9848b48d9c84fe2af5d1d54c1a212c1 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"They collected tweets in Russian language using a heuristic query specific to Russian"
] | task460-3797288ce6bf4800a68b483ffb22c6e3 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Intelligence Squared Debates"
] | task460-1eb7561a85d24473964748d79a15a028 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Yes"
] | task460-6c1a7123d2404314bdc830586b529ffd |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Conditional Random Fields BiLSTM-CRF Multi-Task Learning BioBERT"
] | task460-bf366b6c165b4387b130fcc7fc407bb4 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"2000 sentences"
] | task460-9962f3e6b0fb42479b4fc9f9a0deffea |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"First, the embedding matrix INLINEFORM4 for all corpora is initialized during the training phase, INLINEFORM9 can be used to bias the input feature Next, we apply the language specific softmax to compute logits INLINEFORM4 and optimize them with the CTC objective"
] | task460-812830ed2e2c43baa392534c1d5274de |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"CNN/DailyMail news highlights New York Times Annotated Corpus XSum"
] | task460-4711feb82e8248d9b96a3dbdc1cf11cf |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"CrowdFlower"
] | task460-a7eac29927dc43d3919814b7f342cadf |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"weighted factorization of a word-context co-occurrence matrix "
] | task460-cb730d73ce174d8d9f93c7861cc87565 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Yes"
] | task460-76e27272ce764d218e20516bfad5ed58 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"the attention model, MDREA, also outperforms the best existing research results (WAP 0.690 to 0.688)"
] | task460-27531740c66b4f8bac2ce152f2b84510 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"10,000 Arabic tweet dataset "
] | task460-32362a4b45454d8b95f73454b6571a80 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"modeled the relationship between word count and the two metrics of user engagement (overall rating, mean number of turns) in separate linear regressions"
] | task460-10408992397c4648accd8e3af5fe4bd5 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"the CMU ARCTIC database BIBREF33 the M-AILABS speech dataset BIBREF34 "
] | task460-c9dafba67e614048be0d5594c1675729 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"speaker systems in the real world"
] | task460-f0136972fcd94c16b48812962574591f |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Logistic regression LSTM End-to-end memory networks Deep projective reader"
] | task460-1ac31e06da3049abb19a6aba0973545c |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"Named Entity Recognition"
] | task460-547012511f6147a697e6dbc40b034bf2 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"They exclude slot-specific parameters and incorporate better feature representation of user utterance and dialogue states using syntactic information and convolutional neural networks (CNN)."
] | task460-fa94ca84ab57429093c6b1c4c81da76d |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"KL-divergences of language models for the news article and the already added news references"
] | task460-e1385c023725403080a92623618f90f9 |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Positive Example 1 -
Input: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequ... | [
"We also evaluate all five models on downstream tasks from the VecEval suite BIBREF13 , using only the tasks for which training and evaluation data is freely available: chunking, sentiment and question classification, and natural language identification (NLI). The default settings from the suite are used, but we ru... | task460-7dcef33ad007469b89025e97787f4569 |
End of preview. Expand in Data Studio
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task460_qasper_answer_generation
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks},
author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi},
year={2022},
eprint={2204.07705},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2204.07705},
}
More details can also be found in the following paper:
@misc{brüelgabrielsson2024compressserveservingthousands,
title={Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead},
author={Rickard Brüel-Gabrielsson and Jiacheng Zhu and Onkar Bhardwaj and Leshem Choshen and Kristjan Greenewald and Mikhail Yurochkin and Justin Solomon},
year={2024},
eprint={2407.00066},
archivePrefix={arXiv},
primaryClass={cs.DC},
url={https://arxiv.org/abs/2407.00066},
}
Contact Information
For any comments or questions, please email Rickard Brüel Gabrielsson
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Homepage:
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Paper:
arxiv.org
Point of Contact:
Rickard Brüel Gabrielsson
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