wanyu/IteraTeR_v2 huggingface dataset:
Original:  As a result, the algorithm simultaneously achieves the optimal smooth/non-smooth min-max convergence rates, i.e., it converges to an \varepsilon-optimal solution within O(1/\varepsilon) iterations in smooth problems, and within O(1/\varepsilon^2) iterations in non-smooth ones.
Revised:  As a result, the algorithm simultaneously achieves order-optimal convergence rates, i.e., it converges to an \varepsilon-optimal solution within O(1/\varepsilon) iterations in smooth problems, and within O(1/\varepsilon^2) iterations in non-smooth ones.
Edit intent: clarity
Original:  This "off-the-shelf" adaptation is achieved through the use of a geometric apparatus based on Finsler metrics and a suitably chosen mirror-prox template that allows us to derive sharp convergence rates for the family of methods at hand.
Revised:  This adaptation is achieved through the use of a geometric apparatus based on Finsler metrics and a suitably chosen mirror-prox template that allows us to derive sharp convergence rates for the family of methods at hand.
Edit intent: clarity
Original:  This "off-the-shelf" adaptation is achieved through the use of a geometric apparatus based on Finsler metrics and a suitably chosen mirror-prox template that allows us to derive sharp convergence rates for the family of methods at hand.
Revised:  This "off-the-shelf" adaptation is achieved through the use of a geometric apparatus based on Finsler metrics and a suitably chosen mirror-prox template that allows us to derive sharp convergence rates for the methods at hand.
Edit intent: clarity
Original:  Over-the-air computation, as a new diagram of sensor networks, integrates data collection and processing in one slot: all nodes transmit their signals simultaneously in the analog wave , and the processing is done in the air , by the addition of electromagnetic wave.
Revised:  Over-the-air computation, as a new diagram of sensor networks, integrates data collection and processing in one slot: all nodes transmit their signals simultaneously in the analog wave and the processing is done in the air , by the addition of electromagnetic wave.
Edit intent: fluency
Original:  This is very efficient, but it requires that signals from all nodes arrive at the sink, aligned in signal magnitude so as to enable  unbiased estimation.
Revised:  This is very efficient, but it requires that signals from all nodes arrive at the sink, aligned in signal magnitude so as to enable an unbiased estimation.
Edit intent: fluency
Original:  For a node far away from the sink with a low channel gain, misalignment in signal magnitude is unavoidable.
Revised:  For nodes far away from the sink with a low channel gain, misalignment in signal magnitude is unavoidable.
Edit intent: fluency
Original:  To solve this problem and improve system reliability , in this paper, we investigate the amplify-and-forward based relay .
Revised:  To solve this problem , in this paper, we investigate the amplify-and-forward based relay .
Edit intent: clarity
Original: To better model the contextual information and increase the generalization ability of a voice detection system, this paper leverages a multi-lingual Automatic Speech Recognition (ASR) system to perform Speech Activity Detection (SAD).
Revised: To better model the contextual information and increase the generalization ability of Speech Activity Detection (SAD) system, this paper leverages a multi-lingual Automatic Speech Recognition (ASR) system to perform Speech Activity Detection (SAD).
Edit intent: clarity
Original:  The leveraged multi-lingual ASR is trained on 18 languages of BABEL datasets and the built SAD is evaluated on 3 different languages.
Revised:  The multi-lingual ASR is trained on 18 languages of BABEL datasets and the built SAD is evaluated on 3 different languages.
Edit intent: clarity
Original:  In out-of-domain datasets, the proposed SAD model shows significantly better performance w.r.t. baseline models.
Revised:  On out-of-domain datasets, the proposed SAD model shows significantly better performance w.r.t. baseline models.
Edit intent: fluency
Original:  In out-of-domain datasets, the proposed SAD model shows significantly better performance w.r.t. baseline models.
Revised:  In out-of-domain datasets, the proposed SAD model shows significantly better performance with respect to baseline models.
Edit intent: clarity
Original:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively  7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Revised:  On the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively 7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Edit intent: fluency
Original:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively  7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Revised:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn Rec), and Pyannote baselines (respectively 7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Edit intent: fluency
Original:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively  7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Revised:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively by 7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Edit intent: clarity
Original:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively  7.1, 1.7, and 2.7\% absolutely ) in Detection Error Rate (DetER) metrics.
Revised:  In the Ester2 dataset, without using any in-domain data, this model outperforms the WebRTC, phoneme recognizer based VAD (Phn \_ Rec), and Pyannote baselines (respectively 7.1, 1.7, and 2.7\% absolute ) in Detection Error Rate (DetER) metrics.
Edit intent: fluency
Original:  Similarly, in the LiveATC dataset, this model outperforms the WebRTC, Phn \_ Rec, and Pyannote baselines (respectively  6.4, 10.0, and 3.7\% absolutely) in DetER metrics.
Revised:  Similarly, on the LiveATC dataset, this model outperforms the WebRTC, Phn \_ Rec, and Pyannote baselines (respectively 6.4, 10.0, and 3.7\% absolutely) in DetER metrics.
Edit intent: clarity
Original:  Similarly, in the LiveATC dataset, this model outperforms the WebRTC, Phn \_ Rec, and Pyannote baselines (respectively  6.4, 10.0, and 3.7\% absolutely) in DetER metrics.
Revised:  Similarly, in the LiveATC dataset, this model outperforms the WebRTC, Phn Rec, and Pyannote baselines (respectively 6.4, 10.0, and 3.7\% absolutely) in DetER metrics.
Edit intent: fluency
Original:  Similarly, in the LiveATC dataset, this model outperforms the WebRTC, Phn \_ Rec, and Pyannote baselines (respectively  6.4, 10.0, and 3.7\% absolutely) in DetER metrics.
Revised:  Similarly, in the LiveATC dataset, this model outperforms the WebRTC, Phn \_ Rec, and Pyannote baselines (respectively by 6.4, 10.0, and 3.7\% absolutely) in DetER metrics.
Edit intent: clarity
Original: In agreements among anonymous users, smart contracts eliminate the need for a trusted intermediary and enforce its terms when the conditions set by the parties are met.
Revised: In agreements among anonymous users, smart contract eliminate the need for a trusted intermediary and enforce its terms when the conditions set by the parties are met.
Edit intent: fluency
Original:  The attackers' interaction is formulated as a game and it's shown that the attackers will collaborate in proportion to the amount of their bets .
Revised:  The attackers' interaction as a game and it's shown that the attackers will collaborate in proportion to the amount of their bets .
Edit intent: clarity
Original:  The attackers' interaction is formulated as a game and it's shown that the attackers will collaborate in proportion to the amount of their bets .
Revised:  The attackers' interaction is formulated as a game , and formally prove that these attackers will collaborate in proportion to the amount of their bets .
Edit intent: clarity
Original: The side information of items has been shown to be effective in building the recommendation systems.
Revised: Side information of items has been shown to be effective in building the recommendation systems.
Edit intent: fluency
Original:  Hence, even for researchers  becomes harder and harder to keep track of research topics and their progress.
Revised:  Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress.
Edit intent: fluency
Original:  As an attempt to support human analysts, we present topic space trajectories , a structure that allows for the comprehensible tracking of research topics.
Revised:  As an attempt to support human analysts, we present topic space trajectories , a structure that allows for the comprehensible tracking of research topics.
Edit intent: fluency
Original:  We investigate the closure ordinals of pca's, i.e. \ the smallest ordinals where these relations become equal.
Revised:  We investigate the closure ordinals of pca's, i.e. the smallest ordinals where these relations become equal.
Edit intent: fluency
Original:  We show that the closure ordinal of Kleene's first model is %DIFDELCMD < \OCK %%%  and that the closure ordinal of Kleene's second model is ~ \omega_1.
Revised:  We show that the closure ordinal of Kleene's first model is %DIFDELCMD < \OCK %%% and that the closure ordinal of Kleene's second model is \omega_1.
Edit intent: coherence
Original:  Unlike the direct thought that takes two separated objectives for VAD and speech enhancement respectively, here we propose a new joint optimization objective---VAD-masked scale-invariant source-to-noise ratio (mSI-SDR). mSI-SDR uses VAD information to mask the output of the speech enhancement decoder in the training process.
Revised:  Unlike the direct thought that takes two separated objectives for VAD and speech enhancement respectively, here we propose a new joint optimization objective -- VAD-masked scale-invariant source-to-noise ratio (mSI-SDR). mSI-SDR uses VAD information to mask the output of the speech enhancement decoder in the training process.
Edit intent: fluency
Original: In this work, dynamical systems of points on metric graphs ( a discrete version of a quantum graph with localized wave packets ) that have longest stabilization time are studied.
Revised: A dynamical system of points on metric graphs ( a discrete version of a quantum graph with localized wave packets ) that have longest stabilization time are studied.
Edit intent: clarity
Original: In this work, dynamical systems of points on metric graphs ( a discrete version of a quantum graph with localized wave packets ) that have longest stabilization time are studied.
Revised: In this work, dynamical systems of points on a metric graph is a discrete version of a quantum graph with localized wave packets ) that have longest stabilization time are studied.
Edit intent: fluency
Original:  It is shown that the set of dynamical systems over metric graphs that can be constructed from a given set of edges with fixed lengths  always contains a system consisting of a bead graph with vertex degrees not greater than three that demonstrates longest stabilization time.
Revised:  It is shown that the set of dynamical systems over metric graphs that can be constructed from a given set of edges with fixed lengths . It is shown that such a set always contains a system consisting of a bead graph with vertex degrees not greater than three that demonstrates longest stabilization time.
Edit intent: clarity
Original:  However, natural images - originally intended to be a baseline -  synthetic images by a wide margin (92 \% accuracy).
Revised:  However, natural images - originally intended to be a baseline - outperform these synthetic images by a wide margin (92 \% accuracy).
Edit intent: clarity
Original:  Additionally, participants are faster and more confident for natural images , whereas subjective impressions about the interpretability of feature visualization are mixed .
Revised:  Additionally, participants are faster and more confident for natural images .
Edit intent: clarity
Original:  Even if only a single reference image is given, synthetic images provide less information than natural images (65 \% vs. \pm5\\%DIF > vs. 73 \%).
Revised:  Even if only a single reference image is given, synthetic images provide less information than natural images (65 \pm5\\%DIF > vs. 73 \%).
Edit intent: coherence
Original:  In summary, synthetic images from a popular feature visualization  are significantly less informative for assessing CNN activations than natural images.
Revised:  In summary, synthetic images from a popular feature visualization method are significantly less informative for assessing CNN activations than natural images.
Edit intent: clarity
Original:  We argue that future visualization methods should improve over this simple baseline.
Revised:  We argue that visualization methods should improve over this simple baseline.
Edit intent: clarity
Original:  The experiment is designed to maximize participants' performance, and is the first to probe intermediate instead of final layer representations.
Revised:  The experiments are designed to maximize participants' performance, and is the first to probe intermediate instead of final layer representations.
Edit intent: fluency
Original:  The experiment is designed to maximize participants' performance, and is the first to probe intermediate instead of final layer representations.
Revised:  The experiment is designed to maximize participants' performance, and are the first to probe intermediate instead of final layer representations.
Edit intent: fluency
Original:  However, natural images - originally intended to be a baseline - outperform these %DIF > ).
Revised:  However, natural images - originally intended to be a baseline - %DIF > ).
Edit intent: clarity
Original:  However, natural images - originally intended as a baseline -  synthetic images by a wide margin (92\pm2\\%).
Revised:  However, natural images - originally intended as a baseline - outperform synthetic images by a wide margin (92\pm2\\%).
Edit intent: clarity
Original:  Even if only a single reference image is given, synthetic images provide less information than natural images (65\pm5\\%DIF < vs. 73%DIFDELCMD < \pm4\\%%% %DIF < ).
Revised:  Even if only a single reference image is given, synthetic images provide less information than natural images (65\pm5\\%DIF < vs. %DIFDELCMD < \pm4\\%%% %DIF < ).
Edit intent: clarity
Original:  We argue that visualization methods should improve over this simple baseline.
Revised:  We argue that visualization methods should improve over this baseline.
Edit intent: clarity
Original: Robustly learning in expressive languages with real-world data continues to be a challenging task.
Revised: Robust learning in expressive languages with real-world data continues to be a challenging task.
Edit intent: fluency
Original:  While PAC-Semantics offers strong guarantees, learning explicit representations is not tractable even in a propositional setting .
Revised:  While PAC-Semantics offers strong guarantees, learning explicit representations is not tractable , even in propositional logic .
Edit intent: clarity
Original:  However, the vast majority of the literature was focused on predicting separable Hamiltonian systems with their kinematic and potential energy terms being explicitly decoupled , while building data-driven paradigms to predict nonseparable Hamiltonian systems that are ubiquitous in fluid dynamics and quantum mechanics were rarely explored.
Revised:  However, the vast majority of the literature was focused on predicting separable Hamiltonian systems with their kinematic and potential energy terms being explicitly decoupled while building data-driven paradigms to predict nonseparable Hamiltonian systems that are ubiquitous in fluid dynamics and quantum mechanics were rarely explored.
Edit intent: fluency
Original:  The main computational challenge lies in the effective embedding of symplectic priors to describe the inherently coupled evolution of position and momentum, which typically exhibits intricate dynamics with many degrees of freedom .
Revised:  The main computational challenge lies in the effective embedding of symplectic priors to describe the inherently coupled evolution of position and momentum, which typically exhibits intricate dynamics .
Edit intent: clarity
Original:  We demonstrated the efficacy and versatility of our method by predicting a wide range of Hamiltonian systems, both separable and nonseparable, including vortical flow and quantum system .
Revised:  We demonstrated the efficacy and versatility of our method by predicting a wide range of Hamiltonian systems, both separable and nonseparable, including chaotic vortical flows .
Edit intent: clarity
Original: Randomized higher-order computation can be seen as being captured by a \lambda-calculus endowed with a single algebraic operation, namely a construct for binary probabilistic choice.
Revised: Randomized higher-order computation can be seen as being captured by a lambda calculus endowed with a single algebraic operation, namely a construct for binary probabilistic choice.
Edit intent: fluency
Original:  What matters about such computations is the probability of obtaining any given result, rather than the possibility or thenecessity of obtaining it, like in (non)deterministic computation.
Revised:  What matters about such computations is the probability of obtaining any given result, rather than the possibility or thenecessity of obtaining it, like in (non)deterministic computation.
Edit intent: fluency
Original:  What matters about such computations is the probability of obtaining any given result, rather than the possibility or thenecessity of obtaining it, like in (non)deterministic computation.
Revised:  What matters about such computations is the probability of obtaining any given result, rather than the or thenecessity of obtaining it, like in (non)deterministic computation.
Edit intent: clarity
Original:  What matters about such computations is the probability of obtaining any given result, rather than the possibility or thenecessity of obtaining it, like in (non)deterministic computation.
Revised:  What matters about such computations is the probability of obtaining any given result, rather than the possibility necessity of obtaining it, like in (non)deterministic computation.
Edit intent: fluency
Original:  What matters about such computations is the probability of obtaining any given result, rather than the possibility or thenecessity of obtaining it, like in (non)deterministic computation.
Revised:  What matters about such computations is the probability of obtaining any given result, rather than the possibility or thepossibility or the necessity of obtaining it, like in (non)deterministic computation.
Edit intent: fluency
Original:  In this paper, we show that intersection types are capable of precisely characterizing both notions of termination inside a single system of types: the probability of convergence of any \lambda-term can be underapproximated by its type , while the underlying derivation's weight gives a lower bound to the term's expected number of steps to normal form.
Revised:  In this paper, we show that intersection types are capable of precisely characterizing both notions of termination inside a single system of types: the probability of convergence of any \lambda-term can be underapproximated by its type , while the underlying derivation's weight gives a lower bound to the term's expected number of steps to normal form.
Edit intent: fluency
Original:  In this paper, we show that intersection types are capable of precisely characterizing both notions of termination inside a single system of types: the probability of convergence of any \lambda-term can be underapproximated by its type , while the underlying derivation's weight gives a lower bound to the term's expected number of steps to normal form.
Revised:  In this paper, we show that intersection types are capable of precisely characterizing both notions of termination inside a single system of types: the probability of convergence of any lambda-term can be underapproximated by its type , while the underlying derivation's weight gives a lower bound to the term's expected number of steps to normal form.
Edit intent: fluency
Original:  Noticeably, both approximations are tight---not only soundness but also completeness holds.
Revised:  Noticeably, both approximations are tight -- not only soundness but also completeness holds.
Edit intent: fluency
Original:  Besides, the kind of approximation we obtain is proved to be \emph{optimal recursion theoretically: no recursively enumerable formal system can do better than that.
Revised:  Besides, the kind of approximation we obtain is proved to be \emph{optimal recursion theoretically: no recursively enumerable formal system can do better than that.
Edit intent: fluency
Original:  In addition, we propose a cross modality excitation module to conduct sample-specific activations on acoustic embedding dimensions and adaptively recalibrate the corresponding values by latent semantic features .
Revised:  In addition, we propose a cross modality excitement module to conduct sample-specific activations on acoustic embedding dimensions and adaptively recalibrate the corresponding values by latent semantic features .
Edit intent: fluency
Original:  In addition, we propose a cross modality excitation module to conduct sample-specific activations on acoustic embedding dimensions and adaptively recalibrate the corresponding values by latent semantic features .
Revised:  In addition, we propose a cross modality excitation module to conduct sample-specific adjustment on cross modality embeddings and adaptively recalibrate the corresponding values by latent semantic features .
Edit intent: clarity
Original:  A range query on this structure has to seek and sort-merge data from multiple table files on the fly, which is expensive and often leads to mediocre read performance.
Revised:  Range queries on traditional LSM-trees must seek and sort-merge data from multiple table files on the fly, which is expensive and often leads to mediocre read performance.
Edit intent: clarity
Original:  To improve range query efficiency on LSM-trees, we introduce a space-efficient KV index data structure, named REMIX, that records a global sorted view of KV data spanning multiple table files.
Revised:  To improve range query efficiency on LSM-trees, we introduce a space-efficient KV index data structure, named REMIX, that records a globally sorted view of KV data spanning multiple table files.
Edit intent: fluency
Original:  A range query with REMIX on multiple data files can quickly locate the target key using a binary search, and retrieve the subsequent keys in the sorted order without key comparisons.
Revised:  A range query on multiple REMIX-indexed data files can quickly locate the target key using a binary search, and retrieve the subsequent keys in the sorted order without key comparisons.
Edit intent: clarity
Original:  A range query with REMIX on multiple data files can quickly locate the target key using a binary search, and retrieve the subsequent keys in the sorted order without key comparisons.
Revised:  A range query with REMIX on multiple data files can quickly locate the target key using a binary search, and retrieve subsequent keys in the sorted order without key comparisons.
Edit intent: fluency