| Unlearning What Matters: Token-Level Attribution for Precise Language Model Unlearning added by Syntology |
2026-05 (from id) |
nlp-uoregon/trankit/trankit/layers/crf_layer.py f9126d3e4828acad |
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Apache-2.0 (permissive) |
| arXiv:2507.12075 |
2025-07 (from id) |
booknlp/booknlp/booknlp/common/crf.py 457e7ee196816a9e |
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MIT (permissive) |
| Graph Diffusion Policy Optimization |
26 Feb 2024 |
sail-sg/gdpo/model/infomax.py c03feba6bc4986f6 |
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| Counterfactual Generation with Identifiability Guarantees |
23 Feb 2024 |
hanqi-qi/matte/models/flow_network.py e2a46cef5131cdc0 |
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| Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering |
2 Nov 2023 |
klee972/exec-filter/wikitable/weaksp_em19/wikitable/model/baseline.py 3d7631fc6903e509 |
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| Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering |
2 Nov 2023 |
klee972/exec-filter/wikitable/weaksp_em19/wikitable/module/lattice.py c9cc0b6ea0723393 |
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Apache-2.0 (permissive) |
| RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling |
16 Oct 2023 |
trustedllm/regavae/Step1/train_utils.py 5efe6eb2209f6591 |
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| TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series |
2 Oct 2023 |
ServiceNow/TACTiS/tactis/model/flow.py 3545580aca8bb732 |
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| Exchanging-based Multimodal Fusion with Transformer |
5 Sep 2023 |
recklessronan/muse/code/models.py a42f23f7210ea856 |
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| Language Model Pre-Training with Sparse Latent Typing |
23 Oct 2022 |
renll/sparselt/evaluations/supervised-ie/model.py bd9ad74746bdeace |
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| Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence |
7 Sep 2022 |
idea-ccnl/fengshenbang-lm/fengshen/models/DAVAE/DAVAEModel.py 5efe6eb2209f6591 |
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| Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation |
13 Jul 2022 |
OpenVLG/DELLA/train_utils.py 5efe6eb2209f6591 |
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MIT (permissive) |
| TAGPRIME: A Unified Framework for Relational Structure Extraction |
25 May 2022 |
PlusLabNLP/TagPrime/src/model.py bd9ad74746bdeace |
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| Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks |
28 Jan 2022 |
SCccc21/Knowledge-Enriched-DMI/attack.py 265774c3878176e5 |
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MIT (permissive) |
| Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness |
24 Oct 2021 |
smilesdzgk/du-vae/modules/vae.py 5efe6eb2209f6591 |
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| ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification |
24 Aug 2021 |
apardyl/protomil/weight_loss.py d90a16e645700743 |
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MIT (permissive) |
| Rethinking Noisy Label Models: Labeler-Dependent Noise with Adversarial Awareness |
28 May 2021 |
wohlert/semi-supervised-pytorch/semi-supervised/utils.py c96d37e6f13ff9af |
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MIT (permissive) |
| Video Corpus Moment Retrieval with Contrastive Learning |
13 May 2021 |
IsaacChanghau/ReLoCLNet/method_tvr/contrastive.py 80b5572ac3d22dd3 |
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MIT (permissive) |
| Active Learning for Deep Object Detection via Probabilistic Modeling |
30 Mar 2021 |
NVlabs/AL-MDN/layers/modules/multibox_loss_gmm.py 99c65fd4e843a6a0 |
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| Contrastive Learning with Hard Negative Samples |
9 Oct 2020 |
joshr17/HCL/graph/cortex_DIM/functions/gan_losses.py c03feba6bc4986f6 |
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MIT (permissive) |
| Knowledge-Enriched Distributional Model Inversion Attacks |
8 Oct 2020 |
scccc21/knowledge-enriched-dmi/k+1_gan.py ed2c8f941b766ebb |
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MIT (permissive) |
| Discontinuous Constituent Parsing as Sequence Labeling |
1 Oct 2020 |
aghie/disco2labels/NCRF/model/crf.py 8e960fbb64668568 |
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MIT (permissive) |
| Fast and Accurate Neural CRF Constituency Parsing |
9 Aug 2020 |
jiesutd/NCRFpp/model/crf.py 8e960fbb64668568 |
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| CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information |
22 Jun 2020 |
Linear95/CLUB/mi_estimators.py a1572564f4e423a2 |
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| MAVEN: A Massive General Domain Event Detection Dataset |
28 Apr 2020 |
THU-KEG/MAVEN-dataset/baselines/BERT+CRF/BERT-CRF-MAVEN/crf.py 8e960fbb64668568 |
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MIT (permissive) |
| A Batch Normalized Inference Network Keeps the KL Vanishing Away |
27 Apr 2020 |
valdersoul/bn-vae/modules/utils.py 5efe6eb2209f6591 |
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MIT (permissive) |
| State-only Imitation with Transition Dynamics Mismatch |
27 Feb 2020 |
tgangwani/RL-Indirect-imitation/i2l/networks/discriminator_model.py 5e0544169ee07211 |
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| Parsing as Pretraining |
5 Feb 2020 |
aghie/parsing-as-pretraining/NCRFpp/model/crf.py 8e960fbb64668568 |
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MIT (permissive) |
| Hierarchical Contextualized Representation for Named Entity Recognition |
6 Nov 2019 |
cslydia/Hire-NER/model/crf.py 8e960fbb64668568 |
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Apache-2.0 (permissive) |
| Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning |
4 Jun 2019 |
v-mipeng/LexiconNER/sub_model.py 390527929922fd01 |
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Apache-2.0 (permissive) |
| Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling |
4 Apr 2019 |
kingofspace0wzz/wae-rnf-lm/model.py 7b95c648cb0fb5f2 |
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MIT (permissive) |
| Are Few-Shot Learning Benchmarks too Simple ? Solving them without Task Supervision at Test-Time |
22 Feb 2019 |
gabrielhuang/centroid-networks/protonets/models/wasserstein.py 62fa5972227f4654 |
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MIT (permissive) |
| Wasserstein Barycenter Model Ensembling |
13 Feb 2019 |
IBM/wasserstein-barycenters/barycenter.py 961877103f86fea9 |
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Apache-2.0 (permissive) |
| Particle Flow Bayes' Rule |
2 Feb 2019 |
xinshi-chen/MetaParticleFlow/pfbayes/common/torch_utils.py 4c56e632880df4e3 |
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MIT (permissive) |
| Lagging Inference Networks and Posterior Collapse in Variational Autoencoders |
16 Jan 2019 |
jxhe/vae-lagging-encoder/modules/utils.py 5efe6eb2209f6591 |
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MIT (permissive) |
| Self-Supervised GANs via Auxiliary Rotation Loss |
27 Nov 2018 |
vandit15/Self-Supervised-Gans-Pytorch/ops.py 6a0d455dcdcf2ec5 |
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MIT (permissive) |
| Self-Supervised GANs via Auxiliary Rotation Loss |
27 Nov 2018 |
zhangqianhui/Self-Supervised-GANs/ops.py dffe333c7a3624a0 |
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Apache-2.0 (permissive) |
| BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding |
11 Oct 2018 |
sberbank-ai/ner-bert/modules/layers/ncrf.py 8e960fbb64668568 |
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MIT (permissive) |
| BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding |
11 Oct 2018 |
sberbank-ai/ner-bert/modules/layers/crf.py 913ba2502c2a2780 |
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MIT (permissive) |
| Diverse feature visualizations reveal invariances in early layers of deep neural networks |
27 Jul 2018 |
sacadena/diverse_feature_vis/pixel-cnn/pixel_cnn_pp/nn.py ba937f5383eb9016 |
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MIT (permissive) |
| ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech |
19 Jul 2018 |
tiberiu44/TTS-Cube/cube/networks/loss.py a42f23f7210ea856 |
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Apache-2.0 (permissive) |
| NCRF++: An Open-source Neural Sequence Labeling Toolkit |
14 Jun 2018 |
jiesutd/PyTorchSeqLabel/model/crf.py 8e960fbb64668568 |
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| Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection |
1 Jun 2018 |
thu-spmi/Inclusive-NRF/pytorch_generation/CIFAR_NRF_supervised.py 79526833a41be6f5 |
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| Smooth Loss Functions for Deep Top-k Classification |
21 Feb 2018 |
oval-group/smooth-topk/topk/polynomial/sp.py 17dff13c779067fd |
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MIT (permissive) |
| Towards Deeper Understanding of Variational Autoencoding Models |
28 Feb 2017 |
ShengjiaZhao/Generalized-PixelVAE/pixel_cnn_pp/nn.py ad066f5de5f84073 |
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MIT (permissive) |
| Neural Architectures for Named Entity Recognition |
4 Mar 2016 |
ZubinGou/NER-BiLSTM-CRF-PyTorch/src/model.py d4329236872658c9 |
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MIT (permissive) |
| Neural Architectures for Named Entity Recognition |
4 Mar 2016 |
yyHaker/NamedEntityRecognition/src/LSTM-CNNs-CRF/model.py ca4d0de367bcc625 |
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| End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF |
4 Mar 2016 |
identical code first harvested elsewhere d4329236872658c9 |
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| Named Entity Recognition with Bidirectional LSTM-CNNs |
26 Nov 2015 |
identical code first harvested elsewhere d4329236872658c9 |
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| Bidirectional LSTM-CRF Models for Sequence Tagging |
9 Aug 2015 |
jidasheng/bi-lstm-crf/bi_lstm_crf/model/crf.py 270d6bd48a51f2ae |
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MIT (permissive) |
| Transition-Based Dependency Parsing with Stack Long Short-Term Memory |
29 May 2015 |
mstrise/dep2label/model/crf.py 8e960fbb64668568 |
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MIT (permissive) |
| arXiv:2024.naacl-long.343 |
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king-yyf/CMeKG_tools/model_cws/crf.py 390527929922fd01 |
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MIT (permissive) |
| arXiv:2024.naacl-long.343 |
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king-yyf/CMeKG_tools/model_ner/crf.py 8c72bb90ead60151 |
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MIT (permissive) |
| arXiv:2024.naacl-long.241 |
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jiadongzh/iacos/modelx/rnnx.py 05c860970db7fdc1 |
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Apache-2.0 (permissive) |
| arXiv:2024.findings-acl.760 |
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ej0cl6/TextEE/TextEE/models/AMRIE/E2Emodel.py bd9ad74746bdeace |
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| arXiv:2023.emnlp-demo.11 |
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jiesutd/YATO/model/crf.py 8e960fbb64668568 |
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