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meng jiang university of notre dame dm2 lab home publications activities meng jiang hi i am an associate professor and frank m freimann collegiate professor of computer science and engineering at the university of notre dame i m appointed as a lucy family institute fellow as well as the program chair of nd ibm tech ethics lab my research fields are ai and data science i m interested in developing strong controllable multimodal ai for applications such as sciences e g material discovery math reasoning and engineering e g physical systems recommender systems as well as education and mental health typical approaches are tuning multimodal ai to gain knowledge and skills and precisely follow complex instructions generalizing multimodal ai capabilities with multi objective reinforcement learning controlling multimodal ai to act under moral ethical or rational guidelines adapting multimodal ai efficiently for challenging tasks such as personalization and scientific discovery i am directing the data mining towards decision making dm2 lab as well as the foundation models and applications faml lab at lucy family institute faml is looking for one postdoc to begin in 2027 the research topic emphasizes interdisciplinary collaborations to apply please visit this link drop me an e mail if you are interested what s new june 2026 gang liu has successfully passed his dissertation defense and will join the city university of hong kong as an assistant professor congratulations dr liu may 2026 mengxia yu has successfully passed her dissertation defense and will join apple congratulations dr yu april 2026 welcome jinduo guo and chuhan wang to join our lab and the cse phd program in fall 2026 january 2026 jim and i are organizing the physical ai working group supported by the data ai and computing dac initiative at the university of notre dame let us know if you are interested in the group activities january 2026 scientific ai winter school at the university of puerto rico was successful we presented the work of learning and reasoning for molecular inverse design december 2025 welcome weijiang vicky li to join our lab and the cse phd program in january 2026 gang liu with great work on ai for science is on the academic job market october 2025 we re proud to announce that coefficient giving is supporting our work on ai safety probing guided robust unlearning latest publications replicatorbench benchmarking llm agents on replicability studies in social and behavioral sciences kdd 2026 ai4sciences spectra spectral domain aware graph generation for imbalanced molecular property regression kdd 2026 ai4sciences composing policy gradients and prompt optimization for language model programs cais 2026 dossier deep research via ledger driven branching search and query encoding learning cais 2026 mmtutorbench the first multimodal benchmark for ai math tutoring acl 2026 instant personalized large language model adaptation via hypernetwork acl 2026 mitigating lost in multi turn conversation via curriculum rl with verifiable accuracy and abstention rewards acl 2026 autorubric rubric based generative rewards for faithful multimodal reasoning findings of acl 2026 do llms catch their own mistakes a comprehensive benchmark for reflective tool use llms findings of acl 2026 mtmcs bench evaluating contextual safety of multimodal large language models in multi turn dialogues findings of acl 2026 agentic conversational search with contextualized reasoning via reinforcement learning findings of acl 2026 language coupled reinforcement learning for multilingual retrieval augmented generation findings of acl 2026 crepe a mobile screen data collector using graph query chi 2026 learning to optimize multi objective alignment through dynamic reward weighting tacl 2026 graph diffusion transformers are in context molecular designers iclr 2026 dual space smoothness for robust and balanced llm unlearning iclr 2026 gepa reflective prompt evolution can outperform reinforcement learning iclr 2026 context selection and rewriting for video based educational question generation eaai 2026 learning repetition invariant representations for polymer informatics neurips 2025 pre trained models perform the best when token distributions follow zipf s law emnlp 2025 improving large language models function calling and interpretability via guided structured templates emnlp 2025 leopard a vision language model for text rich multi image tasks tmlr 2025 codetaxo enhancing taxonomy expansion with limited examples via code language prompts findings of acl 2025 qg sms enhancing test item analysis via student modeling and simulation acl 2025 optimizing decomposition for optimal claim verification acl 2025 modality aware neuron pruning for unlearning in multimodal large language models acl 2025 disentangling biased knowledge from reasoning in large language models via machine unlearning acl 2025 aligning large language models with implicit preferences from user generated content acl 2025 enhancing mathematical reasoning in llms by stepwise correction acl 2025 uniconv unifying retrieval and response generation for large language model in conversation acl 2025 protecting privacy in multimodal large language models with mllmu bench naacl 2025 iheval evaluating language models on following the instruction hierarchy naacl 2025 multichartqa benchmarking vision language models on multi chart problems naacl 2025 benchmarking language model creativity a case study on code generation naacl 2025 multimodal large language models for inverse molecular design with retrosynthetic planning iclr 2025 learning molecular representation in a cell iclr 2025 advised phd dissertations daheng wang learning complementarity and dynamics for contextual behavior modeling 2021 tong zhao learning to augment data in graphs 2022 wenhao yu knowledge augmented methods for nlp and beyond 2023 qingkai zeng improving scientific information extraction with text generation 2024 zhihan zhang instructing language models as intelligent assistants 2025 lingbo tong nonlinear structural equation modeling with text data 2025 mengxia yu knowledge enhanced text generation for scientific research and education 2026 gang liu data centric machine learning and foundation models for molecular discovery 2026 last updated on june 30 2026