prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the PaLI model in the PaLI: A Jointly-Scaled Multilingual Language-Image Model paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the BLIP2 model in the What You See is What You Read? Improving Text-Image Alignment Evaluation paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the IAIS large model in the Learning Relation Alignment for Calibrated Cross-modal Retrieval paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the CACR base model in the Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the Diffusion Classifier (zero-shot) model in the Your Diffusion Model is Secretly a Zero-Shot Classifier paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the UNITER large model in the Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the VinVL model in the Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality paper on the Winoground dataset? | Text Score, Image Score, Group Score |
What metrics were used to measure the Humans model in the IRFL: Image Recognition of Figurative Language paper on the IRFL: Image Recognition of Figurative Language dataset? | 1-of-100 Accuracy |
What metrics were used to measure the BEiT-3 model in the Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the X2-VLM (large) model in the X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the XFM (base) model in the Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the CoCa model in the CoCa: Contrastive Captioners are Image-Text Foundation Models paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the X2-VLM (base) model in the X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the VLMo model in the VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the SimVLM model in the SimVLM: Simple Visual Language Model Pretraining with Weak Supervision paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the X-VLM (base) model in the Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the ALBEF (14M) model in the Align before Fuse: Vision and Language Representation Learning with Momentum Distillation paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the UNITER (Large) model in the UNITER: UNiversal Image-TExt Representation Learning paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the SOHO model in the Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the LXMERT model in the LXMERT: Learning Cross-Modality Encoder Representations from Transformers paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the ViLT-B/32 model in the ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision paper on the NLVR2 Test dataset? | Accuracy |
What metrics were used to measure the RPIN model in the Learning Long-term Visual Dynamics with Region Proposal Interaction Networks paper on the PHYRE-1B-Within dataset? | AUCCESS |
What metrics were used to measure the Dynamics-Aware DQN model in the Physical Reasoning Using Dynamics-Aware Models paper on the PHYRE-1B-Within dataset? | AUCCESS |
What metrics were used to measure the Dec[Joint]1f model in the Forward Prediction for Physical Reasoning paper on the PHYRE-1B-Within dataset? | AUCCESS |
What metrics were used to measure the DQN model in the PHYRE: A New Benchmark for Physical Reasoning paper on the PHYRE-1B-Within dataset? | AUCCESS |
What metrics were used to measure the VisualBERT model in the VisualBERT: A Simple and Performant Baseline for Vision and Language paper on the NLVR dataset? | Accuracy (Dev), Accuracy (Test-P), Accuracy (Test-U) |
What metrics were used to measure the Separate And Diffuse model in the Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation paper on the Libri5Mix dataset? | SI-SDRi |
What metrics were used to measure the SepIt model in the SepIt: Approaching a Single Channel Speech Separation Bound paper on the Libri5Mix dataset? | SI-SDRi |
What metrics were used to measure the OCD model in the OCD: Learning to Overfit with Conditional Diffusion Models paper on the Libri5Mix dataset? | SI-SDRi |
What metrics were used to measure the Hungarian PIT model in the Many-Speakers Single Channel Speech Separation with Optimal Permutation Training paper on the Libri5Mix dataset? | SI-SDRi |
What metrics were used to measure the Audio-Visual concat-ref model in the Face Landmark-based Speaker-Independent Audio-Visual Speech Enhancement in Multi-Talker Environments paper on the TCD-TIMIT corpus (mixed-speech) dataset? | SDR |
What metrics were used to measure the Gated DualPathRNN model in the Voice Separation with an Unknown Number of Multiple Speakers paper on the WSJ0-4mix dataset? | SI-SDRi |
What metrics were used to measure the Conditional
TasNet model in the Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals paper on the WSJ0-4mix dataset? | SI-SDRi |
What metrics were used to measure the OR-PIT model in the paper on the WSJ0-4mix dataset? | SI-SDRi |
What metrics were used to measure the Multi-Decoder DPRNN model in the Multi-Decoder DPRNN: High Accuracy Source Counting and Separation paper on the WSJ0-4mix dataset? | SI-SDRi |
What metrics were used to measure the Audio-Visual concat-ref model in the Face Landmark-based Speaker-Independent Audio-Visual Speech Enhancement in Multi-Talker Environments paper on the GRID corpus (mixed-speech) dataset? | SDR |
What metrics were used to measure the MossFormer (L) + DM model in the MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the TD-Conformer (XL) + DM model in the On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Improved Sudo rm -rf (U=36) model in the Compute and memory efficient universal sound source separation paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the TD-Conformer (L) + DM model in the On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Wavesplit model in the Wavesplit: End-to-End Speech Separation by Speaker Clustering paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the DPTNET - SRSSN model in the Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the DPRNN - SRSSN model in the Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the VSUNOS model in the Voice Separation with an Unknown Number of Multiple Speakers paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Sudo rm -rf (U=16) model in the Sudo rm -rf: Efficient Networks for Universal Audio Source Separation paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the TD-Confomer (M) + DM model in the On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Deformable TCN + Dynamic Mixing model in the Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the TD-Confomer (S) model in the On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Deformable TCN + Shared Weights + Dynamic Mixing model in the Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Bi-LSTM-TASNET model in the WHAM!: Extending Speech Separation to Noisy Environments paper on the WHAMR! dataset? | SI-SDRi, MACs (G), Number of parameters (M), SDRi |
What metrics were used to measure the Separate And Diffuse model in the Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation paper on the Libri20Mix dataset? | SI-SDRi |
What metrics were used to measure the Hungarian PIT model in the Many-Speakers Single Channel Speech Separation with Optimal Permutation Training paper on the Libri20Mix dataset? | SI-SDRi |
What metrics were used to measure the Separate And Diffuse model in the Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation paper on the Libri2Mix dataset? | SI-SDRi, SDRi |
What metrics were used to measure the TDANet Large model in the An efficient encoder-decoder architecture with top-down attention for speech separation paper on the Libri2Mix dataset? | SI-SDRi, SDRi |
What metrics were used to measure the TDANet model in the An efficient encoder-decoder architecture with top-down attention for speech separation paper on the Libri2Mix dataset? | SI-SDRi, SDRi |
What metrics were used to measure the Conv-Tasnet (Libri1Mix speech enhancement pre-trained) model in the Stabilizing Label Assignment for Speech Separation by Self-supervised Pre-training paper on the Libri2Mix dataset? | SI-SDRi, SDRi |
What metrics were used to measure the Conv-Tasnet (Libri1Mix speech enhancement multi-task) model in the Stabilizing Label Assignment for Speech Separation by Self-supervised Pre-training paper on the Libri2Mix dataset? | SI-SDRi, SDRi |
What metrics were used to measure the Conv-Tasnet model in the Stabilizing Label Assignment for Speech Separation by Self-supervised Pre-training paper on the Libri2Mix dataset? | SI-SDRi, SDRi |
What metrics were used to measure the CTCNet model in the An Audio-Visual Speech Separation Model Inspired by Cortico-Thalamo-Cortical Circuits paper on the VoxCeleb2 dataset? | SI-SNRi |
What metrics were used to measure the CTCNet model in the An Audio-Visual Speech Separation Model Inspired by Cortico-Thalamo-Cortical Circuits paper on the LRS2 dataset? | SI-SNRi |
What metrics were used to measure the CTCNet model in the An Audio-Visual Speech Separation Model Inspired by Cortico-Thalamo-Cortical Circuits paper on the LRS3 dataset? | SI-SNRi |
What metrics were used to measure the Separate And Diffuse model in the Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the MossFormer (L) + DM model in the MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the MossFormer (M) + DM model in the MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the SepIt model in the SepIt: Approaching a Single Channel Speech Separation Bound paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the SepFormer model in the Attention is All You Need in Speech Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Wavesplit v2 model in the Wavesplit: End-to-End Speech Separation by Speaker Clustering paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the DPTNet (Libri1Mix speech enhancement pre-trained) model in the Stabilizing Label Assignment for Speech Separation by Self-supervised Pre-training paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the TD-Conformer (XL) + DM model in the On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Sandglasset model in the Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the GALR model in the Effective Low-Cost Time-Domain Audio Separation Using Globally Attentive Locally Recurrent Networks paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the DPTNet model in the Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Gated DualPathRNN model in the Voice Separation with an Unknown Number of Multiple Speakers paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Sudo rm -rf (U=36) model in the Compute and memory efficient universal sound source separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Wavesplit v1 model in the Wavesplit: End-to-End Speech Separation by Speaker Clustering paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Sudo rm -rf XL model in the Sudo rm -rf: Efficient Networks for Universal Audio Source Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Dual-path RNN model in the Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the DeepCASA model in the Divide and Conquer: A Deep CASA Approach to Talker-independent Monaural Speaker Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the IAC-PIT Tasnet model in the Interrupted and cascaded permutation invariant training for speech separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Deformable TCN + Dynamic Mixing model in the Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Hybrid-Tasnet model in the Improved Speech Separation with Time-and-Frequency Cross-domain Joint Embedding and Clustering paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Deformable TCN + Shared Weights + Dynamic Mixing model in the Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Two-step Conv-TasNet model in the Two-Step Sound Source Separation: Training on Learned Latent Targets paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Conv-TasNet model in the Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the TasNet v2 model in the Real-time Single-channel Dereverberation and Separation with Time-domainAudio Separation Network paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Chimera++ model in the Alternative Objective Functions for Deep Clustering paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the TasNet model in the TasNet: time-domain audio separation network for real-time, single-channel speech separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Deep Clustering ++ model in the Deep clustering: Discriminative embeddings for segmentation and separation paper on the WSJ0-2mix dataset? | SI-SDRi, SDRi, Number of parameters (M), MACs (G) |
What metrics were used to measure the Hungarian PIT model in the Many-Speakers Single Channel Speech Separation with Optimal Permutation Training paper on the WSJ0-5mix dataset? | SI-SDRi |
What metrics were used to measure the Conditional
TasNet model in the Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture Signals paper on the WSJ0-5mix dataset? | SI-SDRi |
What metrics were used to measure the TasTas model in the Toward Speech Separation in The Pre-Cocktail Party Problem with TasTas paper on the WSJ0-5mix dataset? | SI-SDRi |
What metrics were used to measure the Gated DualPathRNN model in the Voice Separation with an Unknown Number of Multiple Speakers paper on the WSJ0-5mix dataset? | SI-SDRi |
What metrics were used to measure the Multi-Decoder DPRNN model in the Multi-Decoder DPRNN: High Accuracy Source Counting and Separation paper on the WSJ0-5mix dataset? | SI-SDRi |
What metrics were used to measure the Conformer (large) model in the Continuous Speech Separation with Conformer paper on the LibriCSS dataset? | 0S, 0L, 10%, 20%, 30%, 40% |
What metrics were used to measure the Conformer (base) model in the Continuous Speech Separation with Conformer paper on the LibriCSS dataset? | 0S, 0L, 10%, 20%, 30%, 40% |
What metrics were used to measure the Hungarian PIT model in the Many-Speakers Single Channel Speech Separation with Optimal Permutation Training paper on the Libri15Mix dataset? | SI-SDRi |
What metrics were used to measure the MossFormer (L) + DM model in the MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions paper on the WHAM! dataset? | SI-SDRi |
What metrics were used to measure the TDANet Large model in the An efficient encoder-decoder architecture with top-down attention for speech separation paper on the WHAM! dataset? | SI-SDRi |
What metrics were used to measure the TDANet model in the An efficient encoder-decoder architecture with top-down attention for speech separation paper on the WHAM! dataset? | SI-SDRi |
What metrics were used to measure the MossFormer (L) + DM model in the MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions paper on the WSJ0-3mix dataset? | SI-SDRi |
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