Chandan Singh

Senior Researcher

出版物

表示方法:

- Interpretable Next-token Prediction via the Generalized Induction Head
  
  Eunji Kim, Sriya Mantena, Weiwei Yang, Chandan Singh, Sungroh Yoon, Jianfeng Gao
  
  NeurIPS 2025 | October 2025
  
  Publication
- Bayesian Concept Bottleneck Models with LLM Priors
  
  Jean Feng, Avni Kothari, Luke Zier, Chandan Singh, Yan Shuo Tan
  
  NeurIPS 2025 | September 2025
  
  DOI
- Text Generation Beyond Discrete Token Sampling
  
  Yufan Zhuang, Liyuan Liu, Chandan Singh, Jingbo Shang, Jianfeng Gao
  
  NeurIPS 2025 | May 2025
  
  DOI Publication Publication
- Simplifying DINO via Coding Rate Regularization
  
  Ziyang Wu, Jingyuan Zhang, Druv Pai, XuDong Wang, Chandan Singh, Jianwei Yang, Jianfeng Gao, Yi Ma
  
  ICML 2025 | February 2025
  
  DOI Publication Publication
- Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries
  
  Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Crafting Interpretable Embeddings by Asking LLMs Questions
  
  Vinamra Benara, Chandan Singh, John X. Morris, Richard Antonello, Ion Stoica, Alexander Huth, Jianfeng Gao
  
  NeurIPS 2024 | May 2024
  
  DOI Publication Publication
- Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
  
  Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
  
  ICLR 2024 | November 2023
  
  DOI Publication
- Tree Prompting: Efficient Task Adaptation without Fine-Tuning
  
  Chandan Singh, Jianfeng Gao
  
  EMNLP | November 2023
  
  Publication
- Self-Verification Improves Few-Shot Clinical Information Extraction
  
  Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon
  
  May 2023
  
  Publication
- Explaining Patterns in Data with Language Models via Interpretable Autoprompting
  
  Chandan Singh, Jyoti Aneja, Jianfeng Gao
  
  October 2022
  
  Publication Github プロジェクト
- Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models
  
  Chandan Singh, Jianfeng Gao
  
  September 2022
  
  Publication Github

- Interpretable Next-token Prediction via the Generalized Induction Head
  
  Eunji Kim, Sriya Mantena, Weiwei Yang, Chandan Singh, Sungroh Yoon, Jianfeng Gao
  
  NeurIPS 2025 | October 2025
  
  Publication
- Bayesian Concept Bottleneck Models with LLM Priors
  
  Jean Feng, Avni Kothari, Luke Zier, Chandan Singh, Yan Shuo Tan
  
  NeurIPS 2025 | September 2025
  
  DOI
- Text Generation Beyond Discrete Token Sampling
  
  Yufan Zhuang, Liyuan Liu, Chandan Singh, Jingbo Shang, Jianfeng Gao
  
  NeurIPS 2025 | May 2025
  
  DOI Publication Publication
- Simplifying DINO via Coding Rate Regularization
  
  Ziyang Wu, Jingyuan Zhang, Druv Pai, XuDong Wang, Chandan Singh, Jianwei Yang, Jianfeng Gao, Yi Ma
  
  ICML 2025 | February 2025
  
  DOI Publication Publication
- Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries
  
  Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Crafting Interpretable Embeddings by Asking LLMs Questions
  
  Vinamra Benara, Chandan Singh, John X. Morris, Richard Antonello, Ion Stoica, Alexander Huth, Jianfeng Gao
  
  NeurIPS 2024 | May 2024
  
  DOI Publication Publication
- Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
  
  Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
  
  ICLR 2024 | November 2023
  
  DOI Publication
- Tree Prompting: Efficient Task Adaptation without Fine-Tuning
  
  Chandan Singh, Jianfeng Gao
  
  EMNLP | November 2023
  
  Publication
- Self-Verification Improves Few-Shot Clinical Information Extraction
  
  Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon
  
  May 2023
  
  Publication
- Explaining Patterns in Data with Language Models via Interpretable Autoprompting
  
  Chandan Singh, Jyoti Aneja, Jianfeng Gao
  
  October 2022
  
  Publication Github プロジェクト
- Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models
  
  Chandan Singh, Jianfeng Gao
  
  September 2022
  
  Publication Github
- Simplifying DINO via Coding Rate Regularization
  
  Ziyang Wu, Jingyuan Zhang, Druv Pai, XuDong Wang, Chandan Singh, Jianwei Yang, Jianfeng Gao, Yi Ma
  
  ICML 2025 | February 2025
  
  DOI Publication Publication
- Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries
  
  Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Self-Verification Improves Few-Shot Clinical Information Extraction
  
  Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon
  
  May 2023
  
  Publication

- Interpretable Next-token Prediction via the Generalized Induction Head
  
  Eunji Kim, Sriya Mantena, Weiwei Yang, Chandan Singh, Sungroh Yoon, Jianfeng Gao
  
  NeurIPS 2025 | October 2025
  
  Publication
- Bayesian Concept Bottleneck Models with LLM Priors
  
  Jean Feng, Avni Kothari, Luke Zier, Chandan Singh, Yan Shuo Tan
  
  NeurIPS 2025 | September 2025
  
  DOI
- Text Generation Beyond Discrete Token Sampling
  
  Yufan Zhuang, Liyuan Liu, Chandan Singh, Jingbo Shang, Jianfeng Gao
  
  NeurIPS 2025 | May 2025
  
  DOI Publication Publication
- Simplifying DINO via Coding Rate Regularization
  
  Ziyang Wu, Jingyuan Zhang, Druv Pai, XuDong Wang, Chandan Singh, Jianwei Yang, Jianfeng Gao, Yi Ma
  
  ICML 2025 | February 2025
  
  DOI Publication Publication
- Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries
  
  Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Crafting Interpretable Embeddings by Asking LLMs Questions
  
  Vinamra Benara, Chandan Singh, John X. Morris, Richard Antonello, Ion Stoica, Alexander Huth, Jianfeng Gao
  
  NeurIPS 2024 | May 2024
  
  DOI Publication Publication
- Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
  
  Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
  
  ICLR 2024 | November 2023
  
  DOI Publication
- Tree Prompting: Efficient Task Adaptation without Fine-Tuning
  
  Chandan Singh, Jianfeng Gao
  
  EMNLP | November 2023
  
  Publication
- Self-Verification Improves Few-Shot Clinical Information Extraction
  
  Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon
  
  May 2023
  
  Publication
- Explaining Patterns in Data with Language Models via Interpretable Autoprompting
  
  Chandan Singh, Jyoti Aneja, Jianfeng Gao
  
  October 2022
  
  Publication Github プロジェクト
- Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models
  
  Chandan Singh, Jianfeng Gao
  
  September 2022
  
  Publication Github

Chandan Singh

出版物

Interpretable Next-token Prediction via the Generalized Induction Head

Bayesian Concept Bottleneck Models with LLM Priors

Text Generation Beyond Discrete Token Sampling

Simplifying DINO via Coding Rate Regularization

Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries

Crafting Interpretable Embeddings by Asking LLMs Questions

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs

Tree Prompting: Efficient Task Adaptation without Fine-Tuning

Self-Verification Improves Few-Shot Clinical Information Extraction

Explaining Patterns in Data with Language Models via Interpretable Autoprompting

Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models

Interpretable Next-token Prediction via the Generalized Induction Head

Bayesian Concept Bottleneck Models with LLM Priors

Text Generation Beyond Discrete Token Sampling

Simplifying DINO via Coding Rate Regularization

Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries

Crafting Interpretable Embeddings by Asking LLMs Questions

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs

Tree Prompting: Efficient Task Adaptation without Fine-Tuning

Self-Verification Improves Few-Shot Clinical Information Extraction

Explaining Patterns in Data with Language Models via Interpretable Autoprompting

Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models

Simplifying DINO via Coding Rate Regularization

Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries

Self-Verification Improves Few-Shot Clinical Information Extraction

Interpretable Next-token Prediction via the Generalized Induction Head

Bayesian Concept Bottleneck Models with LLM Priors

Text Generation Beyond Discrete Token Sampling

Simplifying DINO via Coding Rate Regularization

Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries

Crafting Interpretable Embeddings by Asking LLMs Questions

Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs

Tree Prompting: Efficient Task Adaptation without Fine-Tuning

Self-Verification Improves Few-Shot Clinical Information Extraction

Explaining Patterns in Data with Language Models via Interpretable Autoprompting

Emb-GAM: an Interpretable and Efficient Predictor using Pre-trained Language Models

お問い合わせ Chandan Singh

Microsoft Research Lab – Redmond