wanyu/IteraTeR_full_sent huggingface dataset:
Original: How to explicitly encode positional information into neural networks is important in learning the representation of natural languages, such as BERT. Based on the Transformer architecture, the positional information is simply encoded as embedding vectors, which are used in the input layer, or encoded as a bias term in the self-attention module. In this work, we investigate the problems in the previous formulations and   propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Revised: In this work, we investigate the positional encoding methods used in language pre-training (e.g., BERT) and identify several problems in the existing formulations. First, we show that in the absolute positional encoding, the addition operation applied on positional embeddings and word embeddings brings mixed correlations between the two heterogeneous information resources. It may bring unnecessary randomness in the attention and further limit the expressiveness of the model. Second, we question whether treating the position of the symbol propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Edit intent: meaning-changed
Original:  In this work, we investigate the problems in the previous formulations and   propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Revised:  In this work, we investigate the problems in the previous formulations and the same as other words is a reasonable design, considering its special role (the representation of the entire sentence) in the downstream tasks. Motivated from above analysis, we propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Edit intent: meaning-changed
Original:  In this work, we investigate the problems in the previous formulations and   propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Revised:  In this work, we investigate the problems in the previous formulations and propose a new positional encoding method for BERT called Transformer with Untied Positional Encodingransformer with (TUPE).
Edit intent: meaning-changed
Original:  In this work, we investigate the problems in the previous formulations and   propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Revised:  In this work, we investigate the problems in the previous formulations and propose a new positional encoding method for BERT called Transformer with Untied Positional Encodingntied (TUPE).
Edit intent: meaning-changed
Original:  In this work, we investigate the problems in the previous formulations and   propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Revised:  In this work, we investigate the problems in the previous formulations and propose a new positional encoding method for BERT called Transformer with Untied Positional Encodingositional (TUPE).
Edit intent: meaning-changed
Original:  In this work, we investigate the problems in the previous formulations and   propose a new positional encoding method for BERT called Transformer with Untied Positional Encoding (TUPE).
Revised:  In this work, we investigate the problems in the previous formulations and propose a new positional encoding method for BERT called Transformer with Untied Positional Encodingncoding (TUPE).
Edit intent: meaning-changed
Original:  This design removes the addition over heterogeneous embeddings in the input, which may potentially bring randomness, and gives more expressiveness to characterize the relationship between words/positions by using different projection matrices.
Revised:  This design removes the mixed and noisy correlations over heterogeneous embeddings in the input, which may potentially bring randomness, and gives more expressiveness to characterize the relationship between words/positions by using different projection matrices.
Edit intent: meaning-changed
Original:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Revised:  Furthermore, TUPE unties the \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Edit intent: style
Original:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Revised:  Furthermore, TUPE unties the CLS \texttt{[CLS symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Edit intent: meaning-changed
Original:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Revised:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions , making it easier to capture information from all positions . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Edit intent: clarity
Original:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Revised:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin.
Edit intent: clarity
Original:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method : TUPE outperforms several baselines on almost all tasks by a large margin. In particular, it can achieve a higher score than baselines while only using 30\% pre-training computational costs. We release our code at URL
Revised:  Furthermore, TUPE unties the CLS \texttt{[ symbol from other positions to provide it with a more specific role to capture the global representation of the sentence . Extensive experiments and ablation studies on GLUE benchmark demonstrate the effectiveness and efficiency of the proposed method . Codes and models are released at URL
Edit intent: clarity
Original:  However, interpretation of the lately proposed models is based on a region of interest and can not be extended to pixel or voxel-wise image interpretation , which is considered to be more informative .
Revised:  However, interpretation of the lately proposed models is based on a region of interest and can not be extended to pixel or voxel-wise image interpretation on a whole image. In the current work, we consider the classification task on a large-scale open-source dataset of young healthy subjects -- an exploration of brain differences between men and women .
Edit intent: meaning-changed
Original:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation and provide the open-source code .
Revised:  We provide the voxel-wise 3D CNN interpretation comparing the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation and provide the open-source code .
Edit intent: meaning-changed
Original:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation and provide the open-source code .
Revised:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, Grad CAM and Guided Backpropagation and provide the open-source code .
Edit intent: fluency
Original:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation and provide the open-source code .
Revised:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation , and contribute with the open-source code .
Edit intent: coherence
Original:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation and provide the open-source code .
Revised:  We compare the results of three voxel-based 3D CNN interpretation methods: Meaningful Perturbations, GradCam and Guided Backpropagation and provide the open-source library .
Edit intent: clarity
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: We devise an algorithm for surveying a dynamic orthogonal polygonal domain\cal \cal , i.e., whenever orthogonal polygon is modified,\cal \cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal P by placing one guard at each vertex in a subset of vertices of\cal , i.e., whenever orthogonal polygon is modified,\cal \cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal P , i.e., whenever orthogonal polygon is modified,\cal \cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal , i.e., whenever an orthogonal polygon domain\cal \cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal , i.e., whenever orthogonal polygon is modified,\cal P' is modified to result in another orthogonal polygonal domain\cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal , i.e., whenever orthogonal polygon is modified,\cal \cal P, our algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal , i.e., whenever orthogonal polygon is modified,\cal \cal algorithm updates the set of (vertex) guards surveying\cal \cal .
Edit intent: clarity
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal , i.e., whenever orthogonal polygon is modified,\cal \cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal P' so that the updated guard set surveys\cal .
Edit intent: meaning-changed
Original: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal  , i.e., whenever orthogonal polygon is modified,\cal \cal  algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal  .
Revised: Given an orthogonal polygon with orthogonal holes, we devise a dynamic algorithm for guarding with vertex guards\cal \cal , i.e., whenever orthogonal polygon is modified,\cal \cal algorithm updates the set of vertex guards and their positions for guarding the modified orthogonal polygon\cal \cal P .
Edit intent: meaning-changed
Original:  Our algorithm modifies the guard placement locally while ensuring the updated orthogonal polygon with h holes and n vertices , is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Revised:  Our algorithm modifies the guard placement in O(k \lg{(n+n') while ensuring the updated orthogonal polygon with h holes and n vertices , is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Edit intent: meaning-changed
Original:  Our algorithm modifies the guard placement locally while ensuring the updated orthogonal polygon with h holes and n vertices , is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Revised:  Our algorithm modifies the guard placement locally while ensuring the updated orthogonal polygon with h holes and n vertices is guarded using at most \lfloor (n+2h)/4 \rfloor vertex guards.
Edit intent: fluency
Original:  and, k is the sum of the number of vertices added to or removed from the orthogonal polygon, the number of cuts in the L-shaped partitioning of the free space of the orthogonal polygon that got affected due to the update, and the number of channels affected due to the update.
Revised:  and, k is the sum of |n - n'| and the number of channels affected due to the update.
Edit intent: meaning-changed
Original:  and, k is the sum of the number of vertices added to or removed from the orthogonal polygon, the number of cuts in the L-shaped partitioning of the free space of the orthogonal polygon that got affected due to the update, and the number of channels affected due to the update. For the special case of the initial orthogonal polygon being hole-free, and each update resulting in a hole-free orthogonal polygon, our dynamic guard updating algorithmtakes O(k\lg{(n+n')) worst-case time.
Revised:  and, k is the sum of the number of vertices added to or removed from the orthogonal polygon, the number of cuts in the L-shaped partitioning of the free space of the orthogonal polygon that got affected due to the update, and the number of ) worst-case time.
Edit intent: meaning-changed
Original:  Initially, we preprocess the input orthogonal polygon with q vertices in O(q \lg{q}) time to construct data structures of size O(q\frac{\lg{q}}{\lg\lg{q}})}  .
Revised:  Initially, we preprocess the input orthogonal polygon with q vertices in O(q \lg{q}) time to construct data structures of size O(q\frac{\lg{q}}{\lg\lg{q}})} updates in a few structures maintained by our algorithm .
Edit intent: meaning-changed
Original:  Growing interests of using pre-trained language models with transfer learning address the issue to some extent . Recently, learning linguistic knowledge of entailment in sentence pairs enhances the performance in general domain QAby leveraging such transferability between the two tasks .
Revised:  Pre-trained language models have been used to address these issues . Recently, learning linguistic knowledge of entailment in sentence pairs enhances the performance in general domain QAby leveraging such transferability between the two tasks .
Edit intent: clarity
Original:  Growing interests of using pre-trained language models with transfer learning address the issue to some extent . Recently, learning linguistic knowledge of entailment in sentence pairs enhances the performance in general domain QAby leveraging such transferability between the two tasks .
Revised:  Growing interests of using pre-trained language models with transfer learning address the issue to some extent . Recently, learning relationships between sentence pairs has been proved to improve performance in general domain QAby leveraging such transferability between the two tasks .
Edit intent: clarity
Original:  Growing interests of using pre-trained language models with transfer learning address the issue to some extent . Recently, learning linguistic knowledge of entailment in sentence pairs enhances the performance in general domain QAby leveraging such transferability between the two tasks .
Revised:  Growing interests of using pre-trained language models with transfer learning address the issue to some extent . Recently, learning linguistic knowledge of entailment in sentence pairs enhances the performance in general QA .
Edit intent: clarity
Original:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List  (+13.58\%) type questions compared to previous challenge reports (BioASQ 7B Phase B).
Revised:  We observe that BioBERT trained on the NLI dataset obtains better performance on Yes/No (+5.59\%), Factoid (+0.53\%), List (+13.58\%) type questions compared to previous challenge reports (BioASQ 7B Phase B).
Edit intent: meaning-changed
Original:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List  (+13.58\%) type questions compared to previous challenge reports (BioASQ 7B Phase B).
Revised:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List type (+13.58\%) type questions compared to previous challenge reports (BioASQ 7B Phase B).
Edit intent: clarity
Original:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List  (+13.58\%) type questions compared to previous challenge reports (BioASQ 7B Phase B).
Revised:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List (+13.58\%) questions compared to previous challenge reports (BioASQ 7B Phase B).
Edit intent: clarity
Original:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List  (+13.58\%) type questions compared to previous challenge reports (BioASQ 7B Phase B).
Revised:  We observe that transferring from entailment data shows effective performance on Yes/No (+5.59\%), Factoid (+0.53\%), List (+13.58\%) type questions compared to performance obtained in a previous challenge (BioASQ 7B Phase B).
Edit intent: clarity
Original:  In factoid- and list-type questions, we thoroughly analyze an intrinsic limitation of the extractive QA setting when these questions are converted to the same format of the Stanford Question Answering Dataset (SQuAD).
Revised:  In factoid- and list-type questions, we thoroughly analyze an intrinsic limitation of the extractive QA setting when the formats of factoid and list type questions are converted to the same format of the Stanford Question Answering Dataset (SQuAD).
Edit intent: clarity
Original:  In factoid- and list-type questions, we thoroughly analyze an intrinsic limitation of the extractive QA setting when these questions are converted to the same format of the Stanford Question Answering Dataset (SQuAD).
Revised:  In factoid- and list-type questions, we thoroughly analyze an intrinsic limitation of the extractive QA setting when these questions are converted to the format of the Stanford Question Answering Dataset (SQuAD).
Edit intent: clarity
Original:  To do so, we have incorporated the kinetics and energetics of memory response as ingredients of non-equilibrium decision-making between an adaptive exploration to mount a specific and novel response or exploitation of existing memory that can be activated rapidly yet with a reduced specificity against evolved pathogens. To achieve a long-term benefit for the host, we show that memory generation should be actively regulated and dependent on immune receptors ' affinity, with a preference for cross-reactive receptors with a moderate affinity against pathogens as opposed to high affinity receptors -
Revised:  We show that memory generation should be actively regulated and dependent on immune receptors ' affinity, with a preference for cross-reactive receptors with a moderate affinity against pathogens as opposed to high affinity receptors -
Edit intent: coherence