Dynamic time-aware attention to speaker roles and contexts for spoken language understanding. - Po-Chun Chen; Ta-Chung Chi; Shang-Yu Su; Yun-Nung Chen (ASRU, 2017)

Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning. - Ta-Chung Chi; Po-Chun Chen; Shang-Yu Su; Yun-Nung Chen (IJCNLP(2), 2017)

CLUSE: Cross-Lingual Unsupervised Sense Embeddings. - Ta-Chung Chi; Yun-Nung Chen (EMNLP, 2018)

xSense: Learning Sense-Separated Sparse Representations and Textual Definitions for Explainable Word Sense Networks. - Ting-Yun Chang; Ta-Chung Chi; Shang-Chi Tsai; Yun-Nung Chen (CoRR, 2018)

BCWS: Bilingual Contextual Word Similarity. - Ta-Chung Chi; Ching-Yen Shih; Yun-Nung Chen (CoRR, 2018)

Just Ask: An Interactive Learning Framework for Vision and Language Navigation. - Ta-Chung Chi; Minmin Shen; Mihail Eric; Seokhwan Kim; Dilek Hakkani-Tür (AAAI, 2020)

Automatic Speech Verification Spoofing Detection. - Shentong Mo; Haofan Wang; Pinxu Ren; Ta-Chung Chi (CoRR, 2020)

Zero-Shot Dialogue Disentanglement by Self-Supervised Entangled Response Selection. - Ta-Chung Chi; Alexander I. Rudnicky (EMNLP (1), 2021)

Are you doing what I say? On modalities alignment in ALFRED. - Ting-Rui Chiang; Yi-Ting Yeh; Ta-Chung Chi; Yau-Shian Wang (CoRR, 2021)

Training Discrete Deep Generative Models via Gapped Straight-Through Estimator. - Ting-Han Fan; Ta-Chung Chi; Alexander I. Rudnicky; Peter J. Ramadge (ICML, 2022)

KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation. - Ta-Chung Chi; Ting-Han Fan; Peter J. Ramadge; Alexander Rudnicky (NeurIPS, 2022)

Structured Dialogue Discourse Parsing. - Ta-Chung Chi; Alexander I. Rudnicky (SIGDIAL, 2022)

On Task-Adaptive Pretraining for Dialogue Response Selection. - Tzu-Hsiang Lin; Ta-Chung Chi; Anna Rumshisky (CoRR, 2022)

Receptive Field Alignment Enables Transformer Length Extrapolation. - Ta-Chung Chi; Ting-Han Fan; Alexander I. Rudnicky (CoRR, 2022)

Latent Positional Information is in the Self-Attention Variance of Transformer Language Models Without Positional Embeddings. - Ta-Chung Chi; Ting-Han Fan; Li-Wei Chen; Alexander Rudnicky; Peter J. Ramadge (ACL (2), 2023)

Dissecting Transformer Length Extrapolation via the Lens of Receptive Field Analysis. - Ta-Chung Chi; Ting-Han Fan; Alexander Rudnicky; Peter J. Ramadge (ACL (1), 2023)

PESCO: Prompt-enhanced Self Contrastive Learning for Zero-shot Text Classification. - Yau-Shian Wang; Ta-Chung Chi; Ruohong Zhang; Yiming Yang (ACL (1), 2023)

Transformer Working Memory Enables Regular Language Reasoning And Natural Language Length Extrapolation. - Ta-Chung Chi; Ting-Han Fan; Alexander Rudnicky; Peter J. Ramadge (EMNLP (Findings), 2023)

Attention Alignment and Flexible Positional Embeddings Improve Transformer Length Extrapolation. - Ta-Chung Chi; Ting-Han Fan; Alexander Rudnicky (NAACL-HLT (Findings), 2024)

Advancing Regular Language Reasoning in Linear Recurrent Neural Networks. - Ting-Han Fan; Ta-Chung Chi; Alexander Rudnicky (NAACL (Short Papers), 2024)

Toward Length-Extrapolatable Transformers - Ta-Chung Chi (2024)