Particle filter for target tracking in multi-modality wireless sensor networks. - Wendong Xiao; Feng Nan; Sen Zhang 001; Chen-Khong Tham; Marcelo H. Ang; Jit Biswas (SMC, 2008)

A Subspace Semi-Definite programming-based Underestimation (SSDU) method for stochastic global optimization in protein docking. - Feng Nan; Mohammad Moghadasi; Pirooz Vakili; Sandor Vajda; Dima Kozakov; Ioannis Ch. Paschalidis (CDC, 2014)

Fast margin-based cost-sensitive classification. - Feng Nan; Joseph Wang 001; Kirill Trapeznikov; Venkatesh Saligrama (ICASSP, 2014)

Feature-Budgeted Random Forest. - Feng Nan; Joseph Wang 001; Venkatesh Saligrama (ICML, 2015)

Max-Cost Discrete Function Evaluation Problem under a Budget. - Feng Nan; Joseph Wang 001; Venkatesh Saligrama (CoRR, 2015)

Pruning Random Forests for Prediction on a Budget. - Feng Nan; Joseph Wang 001; Venkatesh Saligrama (NIPS, 2016)

Optimally Pruning Decision Tree Ensembles With Feature Cost. - Feng Nan; Joseph Wang 001; Venkatesh Saligrama (CoRR, 2016)

Adaptive Classification for Prediction Under a Budget. - Feng Nan; Venkatesh Saligrama (NIPS, 2017)

Dynamic Model Selection for Prediction Under a Budget. - Feng Nan; Venkatesh Saligrama (CoRR, 2017)

Comments on the proof of adaptive submodular function minimization. - Feng Nan; Venkatesh Saligrama (CoRR, 2017)

Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget. - Henghui Zhu; Feng Nan; Ioannis Ch. Paschalidis; Venkatesh Saligrama (CoRR, 2017)

Comments on the Proof of Adaptive Stochastic Set Cover Based on Adaptive Submodularity and Its Implications for the Group Identification Problem in "Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations". - Feng Nan; Venkatesh Saligrama (IEEE Trans. Inf. Theory, 2017)

Real-Time Monitoring of Smart Campus and Construction of Weibo Public Opinion Platform. - Feng Nan; Yina Suo; Xueyong Jia; Yuying Wu; Shuaijie Shan (IEEE Access, 2018)

Topic Modeling with Wasserstein Autoencoders. - Feng Nan; Ran Ding; Ramesh Nallapati; Bing Xiang (ACL (1), 2019)

Who Did They Respond to? Conversation Structure Modeling Using Masked Hierarchical Transformer. - Henghui Zhu; Feng Nan; Zhiguo Wang; Ramesh Nallapati; Bing Xiang (AAAI, 2020)

End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems. - Siamak Shakeri; Cícero Nogueira dos Santos; Henghui Zhu; Patrick Ng; Feng Nan; Zhiguo Wang; Ramesh Nallapati; Bing Xiang (EMNLP (1), 2020)

Unsupervised Domain Adaptation for Cross-lingual Text Labeling. - Dejiao Zhang; Ramesh Nallapati; Henghui Zhu; Feng Nan; Cícero Nogueira dos Santos; Kathleen R. McKeown; Bing Xiang (EMNLP (Findings), 2020)

Back Analysis of Concrete Temperature Field and Simulation of Temperature Control Measures Based on Simulated Annealing Algorithm. - Xuxiang Tan; Huadong Sun; Feng Nan (IWCMC, 2020)

Application of Improved BP Algorithm in Prediction of Axial Tension Performance and Crack Width Control Ability of UHPC. - Xuxiang Tan; Huadong Sun; Feng Nan (IWCMC, 2020)

End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems. - Siamak Shakeri; Cícero Nogueira dos Santos; Henry Zhu; Patrick Ng; Feng Nan; Zhiguo Wang; Ramesh Nallapati; Bing Xiang (CoRR, 2020)

Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction. - Yifan Gao 001; Henghui Zhu; Patrick Ng; Cícero Nogueira dos Santos; Zhiguo Wang; Feng Nan; Dejiao Zhang; Ramesh Nallapati; Andrew O. Arnold; Bing Xiang (ACL/IJCNLP (1), 2021)

Improving Factual Consistency of Abstractive Summarization via Question Answering. - Feng Nan; Cícero Nogueira dos Santos; Henghui Zhu; Patrick Ng; Kathleen R. McKeown; Ramesh Nallapati; Dejiao Zhang; Zhiguo Wang; Andrew O. Arnold; Bing Xiang (ACL/IJCNLP (1), 2021)

Entity-level Factual Consistency of Abstractive Text Summarization. - Feng Nan; Ramesh Nallapati; Zhiguo Wang; Cícero Nogueira dos Santos; Henghui Zhu; Dejiao Zhang; Kathy McKeown; Bing Xiang (EACL, 2021)

Supporting Clustering with Contrastive Learning. - Dejiao Zhang; Feng Nan; Xiaokai Wei; Shang-Wen Li 001; Henghui Zhu; Kathleen R. McKeown; Ramesh Nallapati; Andrew O. Arnold; Bing Xiang (NAACL-HLT, 2021)

Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notes. - Han-Chin Shing; Chaitanya Shivade; Nima Pourdamghani; Feng Nan; Philip Resnik; Douglas W. Oard; Parminder Bhatia (CoRR, 2021)

Analyzing the Abstractiveness-Factuality Tradeoff With Nonlinear Abstractiveness Constraints. - Markus Dreyer; Mengwen Liu; Feng Nan; Sandeep Atluri; Sujith Ravi (CoRR, 2021)

Generation-Focused Table-Based Intermediate Pre-training for Free-Form Question Answering. - Peng Shi 010; Patrick Ng; Feng Nan; Henghui Zhu; Jun Wang 122; Jiarong Jiang; Alexander Hanbo Li; Rishav Chakravarti; Donald Weidner; Bing Xiang; Zhiguo Wang (AAAI, 2022)

Using Structured Content Plans for Fine-grained Syntactic Control in Pretrained Language Model Generation. - Fei-Tzin Lee; Miguel Ballesteros; Feng Nan; Kathleen R. McKeown (COLING, 2022)

ContraGen: Effective Contrastive Learning For Causal Language Model. - Nihal Jain; Dejiao Zhang; Wasi Uddin Ahmad; Zijian Wang 002; Feng Nan; Xiaopeng Li 002; Ming Tan; Ramesh Nallapati; Baishakhi Ray; Parminder Bhatia; Xiaofei Ma 001; Bing Xiang (CoRR, 2022)

ContraCLM: Contrastive Learning For Causal Language Model. - Nihal Jain; Dejiao Zhang; Wasi Uddin Ahmad; Zijian Wang 002; Feng Nan; Xiaopeng Li 002; Ming Tan; Ramesh Nallapati; Baishakhi Ray; Parminder Bhatia; Xiaofei Ma 001; Bing Xiang (ACL (1), 2023)

Evaluating the Tradeoff Between Abstractiveness and Factuality in Abstractive Summarization. - Markus Dreyer; Mengwen Liu; Feng Nan; Sandeep Atluri; Sujith Ravi (EACL (Findings), 2023)

SWING: Balancing Coverage and Faithfulness for Dialogue Summarization. - Kung-Hsiang Huang; Siffi Singh; Xiaofei Ma 001; Wei Xiao 001; Feng Nan; Nicholas Dingwall; William Yang Wang; Kathleen R. McKeown (EACL (Findings), 2023)

Validation and Evaluation of GRACE-FO Estimates with In Situ Bottom Pressure Array Measurements in the South China Sea. - Xuecheng Wang; Hua Zheng; Xiao-Hua Zhu; Ruixiang Zhao; Min Wang; Juntian Chen; Yunlong Ma; Feng Nan; Fei Yu (Remote. Sens., 2023)

Apple Intelligence Foundation Language Models. - Tom Gunter; Zirui Wang; Chong Wang; Ruoming Pang; Andy Narayanan; Aonan Zhang; Bowen Zhang 002; Chen Chen 005; Chung-Cheng Chiu; David Qiu; Deepak Gopinath; Dian Ang Yap; et al. (CoRR, 2024)

ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities. - Jiarui Lu; Thomas Holleis; Yizhe Zhang 002; Bernhard Aumayer; Feng Nan; Felix Bai; Shuang Ma; Shen Ma; Mengyu Li; Guoli Yin; Zirui Wang; Ruoming Pang (CoRR, 2024)

ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities. - Jiarui Lu; Thomas Holleis; Yizhe Zhang 002; Bernhard Aumayer; Feng Nan; Haoping Bai; Shuang Ma; Shen Ma; Mengyu Li; Guoli Yin; Zirui Wang; Ruoming Pang (NAACL (Findings), 2025)

MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains. - Guoli Yin; Haoping Bai; Shuang Ma; Feng Nan; Yanchao Sun; Zhaoyang Xu; Shen Ma; Jiarui Lu; Xiang Kong; Aonan Zhang; Dian Ang Yap; Yizhe Zhang 002; et al. (NAACL (Findings), 2025)

Apple Intelligence Foundation Language Models: Tech Report 2025. - Hanzhi Zhou; Erik Hornberger; Pengsheng Guo; Xiyou Zhou; Saiwen Wang; Xin Wang; Yifei He; Xuankai Chang; Rene Rauch; Louis D'hauwe; John Peebles; Alec Doane; et al. (CoRR, 2025)