1 code implementation • 9 Jun 2025 • Mickel Liu, Liwei Jiang, Yancheng Liang, Simon Shaolei Du, Yejin Choi, Tim Althoff, Natasha Jaques
Conventional language model (LM) safety alignment relies on a reactive, disjoint procedure: attackers exploit a static model, followed by defensive fine-tuning to patch exposed vulnerabilities.
no code implementations • 9 Jun 2025 • Ken Gu, Zhihan Zhang, Kate Lin, Yuwei Zhang, Akshay Paruchuri, Hong Yu, Mehran Kazemi, Kumar Ayush, A. Ali Heydari, Maxwell A. Xu, Girish Narayanswamy, Yun Liu, Ming-Zher Poh, Yuzhe Yang, Mark Malhotra, Shwetak Patel, Hamid Palangi, Xuhai Xu, Daniel McDuff, Tim Althoff, Xin Liu
Language models (LMs) are increasingly being deployed to perform autonomous data analyses.
no code implementations • 5 Jun 2025 • Maxwell A. Xu, Girish Narayanswamy, Kumar Ayush, Dimitris Spathis, Shun Liao, Shyam A. Tailor, Ahmed Metwally, A. Ali Heydari, Yuwei Zhang, Jake Garrison, Samy Abdel-Ghaffar, Xuhai Xu, Ken Gu, Jacob Sunshine, Ming-Zher Poh, Yun Liu, Tim Althoff, Shrikanth Narayanan, Pushmeet Kohli, Mark Malhotra, Shwetak Patel, Yuzhe Yang, James M. Rehg, Xin Liu, Daniel McDuff
Foundation models, a cornerstone of recent advancements in machine learning, have predominantly thrived on complete and well-structured data.
no code implementations • 25 Mar 2025 • Vidya Srinivas, Xuhai Xu, Xin Liu, Kumar Ayush, Isaac Galatzer-Levy, Shwetak Patel, Daniel McDuff, Tim Althoff
While NLP research has made strides in conversational tasks, many approaches focus on single-turn responses with well-defined objectives or evaluation criteria.
1 code implementation • 18 Mar 2025 • Mingtian Tan, Mike A. Merrill, Zack Gottesman, Tim Althoff, David Evans, Tom Hartvigsen
Events are often described with natural language, so we conduct the first study of whether Large Language Models (LLMs) can infer natural language events from time series.
1 code implementation • 11 Feb 2025 • Sahand Sabour, June M. Liu, Siyang Liu, Chris Z. Yao, Shiyao Cui, Xuanming Zhang, Wen Zhang, Yaru Cao, Advait Bhat, Jian Guan, Wei Wu, Rada Mihalcea, Hongning Wang, Tim Althoff, Tatia M. C. Lee, Minlie Huang
Through a randomized controlled trial with 233 participants, we examined human susceptibility to such manipulation in financial (e. g., purchases) and emotional (e. g., conflict resolution) decision-making contexts.
no code implementations • 17 Oct 2024 • Girish Narayanswamy, Xin Liu, Kumar Ayush, Yuzhe Yang, Xuhai Xu, Shun Liao, Jake Garrison, Shyam Tailor, Jake Sunshine, Yun Liu, Tim Althoff, Shrikanth Narayanan, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak Patel, Samy Abdel-Ghaffar, Daniel McDuff
Wearable sensors have become ubiquitous thanks to a variety of health tracking features.
1 code implementation • 19 Aug 2024 • Ken Gu, Ruoxi Shang, Ruien Jiang, Keying Kuang, Richard-John Lin, Donghe Lyu, Yue Mao, Youran Pan, Teng Wu, Jiaqian Yu, Yikun Zhang, Tianmai M. Zhang, Lanyi Zhu, Mike A. Merrill, Jeffrey Heer, Tim Althoff
To address these challenges, we present BLADE, a benchmark to automatically evaluate agents' multifaceted approaches to open-ended research questions.
3 code implementations • 22 Jun 2024 • Mingtian Tan, Mike A. Merrill, Vinayak Gupta, Tim Althoff, Thomas Hartvigsen
Large language models (LLMs) are being applied to time series forecasting.
1 code implementation • 18 Jun 2024 • Akshay Paruchuri, Jake Garrison, Shun Liao, John Hernandez, Jacob Sunshine, Tim Althoff, Xin Liu, Daniel McDuff
Language models (LM) are capable of remarkably complex linguistic tasks; however, numerical reasoning is an area in which they frequently struggle.
no code implementations • 10 Jun 2024 • Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei, Geza Kovacs, Javier Perez, Yun Liu, Erik Schenck, Nova Hammerquist, Jake Sunshine, Shyam Tailor, Kumar Ayush, Hao-Wei Su, Qian He, Cory Y. McLean, Mark Malhotra, Shwetak Patel, Jiening Zhan, Tim Althoff, Daniel McDuff, Xin Liu
Despite the proliferation of wearable health trackers and the importance of sleep and exercise to health, deriving actionable personalized insights from wearable data remains a challenge because doing so requires non-trivial open-ended analysis of these data.
no code implementations • 10 Jun 2024 • Justin Cosentino, Anastasiya Belyaeva, Xin Liu, Nicholas A. Furlotte, Zhun Yang, Chace Lee, Erik Schenck, Yojan Patel, Jian Cui, Logan Douglas Schneider, Robby Bryant, Ryan G. Gomes, Allen Jiang, Roy Lee, Yun Liu, Javier Perez, Jameson K. Rogers, Cathy Speed, Shyam Tailor, Megan Walker, Jeffrey Yu, Tim Althoff, Conor Heneghan, John Hernandez, Mark Malhotra, Leor Stern, Yossi Matias, Greg S. Corrado, Shwetak Patel, Shravya Shetty, Jiening Zhan, Shruthi Prabhakara, Daniel McDuff, Cory Y. McLean
Here we present Personal Health Large Language Model (PH-LLM), fine-tuned from Gemini for understanding and reasoning over numerical time-series personal health data.
no code implementations • 17 Apr 2024 • Mike A. Merrill, Mingtian Tan, Vinayak Gupta, Tom Hartvigsen, Tim Althoff
But it remains unknown whether non-trivial forecasting implies that language models can reason about time series.
1 code implementation • 17 Mar 2024 • Xinyi Zhou, ASHISH SHARMA, Amy X. Zhang, Tim Althoff
High-quality and timely correction of misinformation that identifies and explains its (in)accuracies effectively reduces false beliefs.
1 code implementation • 14 Mar 2024 • Chu Li, Zhihan Zhang, Michael Saugstad, Esteban Safranchik, Minchu Kulkarni, Xiaoyu Huang, Shwetak Patel, Vikram Iyer, Tim Althoff, Jon E. Froehlich
Crowdsourcing platforms have transformed distributed problem-solving, yet quality control remains a persistent challenge.
no code implementations • 19 Feb 2024 • Inna Wanyin Lin, ASHISH SHARMA, Christopher Michael Rytting, Adam S. Miner, Jina Suh, Tim Althoff
With IMBUE's additional just-in-time feedback, participants demonstrate 17% improvement in skill mastery, along with greater enhancements in self-efficacy (27% more) and reduction of negative emotions (16% more) compared to simulation-only.
1 code implementation • 7 Feb 2024 • Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, Yejin Choi
We identify and formalize three possible ways to define and operationalize pluralism in AI systems: 1) Overton pluralistic models that present a spectrum of reasonable responses; 2) Steerably pluralistic models that can steer to reflect certain perspectives; and 3) Distributionally pluralistic models that are well-calibrated to a given population in distribution.
1 code implementation • 1 Jan 2024 • Yu Ying Chiu, ASHISH SHARMA, Inna Wanyin Lin, Tim Althoff
The emergence of large language models (LLMs) like ChatGPT has increased interest in their use as therapists to address mental health challenges and the widespread lack of access to care.
no code implementations • 24 Oct 2023 • ASHISH SHARMA, Kevin Rushton, Inna Wanyin Lin, Theresa Nguyen, Tim Althoff
In an IRB-approved randomized field study on a large mental health website with 15, 531 participants, we design and evaluate a system that uses language models to support people through various steps of cognitive restructuring.
2 code implementations • 4 May 2023 • ASHISH SHARMA, Kevin Rushton, Inna Wanyin Lin, David Wadden, Khendra G. Lucas, Adam S. Miner, Theresa Nguyen, Tim Althoff
In this paper, we conduct a human-centered study of how language models may assist people in reframing negative thoughts.
1 code implementation • 24 Mar 2023 • Suchin Gururangan, Margaret Li, Mike Lewis, Weijia Shi, Tim Althoff, Noah A. Smith, Luke Zettlemoyer
Large language models are typically trained densely: all parameters are updated with respect to all inputs.
1 code implementation • 4 Nov 2022 • Xuhai Xu, Han Zhang, Yasaman Sefidgar, Yiyi Ren, Xin Liu, Woosuk Seo, Jennifer Brown, Kevin Kuehn, Mike Merrill, Paula Nurius, Shwetak Patel, Tim Althoff, Margaret E. Morris, Eve Riskin, Jennifer Mankoff, Anind K. Dey
We envision our multi-year datasets can support the ML community in developing generalizable longitudinal behavior modeling algorithms.
no code implementations • 27 Oct 2022 • Inna Wanyin Lin, Lucille Njoo, Anjalie Field, ASHISH SHARMA, Katharina Reinecke, Tim Althoff, Yulia Tsvetkov
Mental health stigma prevents many individuals from receiving the appropriate care, and social psychology studies have shown that mental health tends to be overlooked in men.
2 code implementations • 5 Aug 2022 • Margaret Li, Suchin Gururangan, Tim Dettmers, Mike Lewis, Tim Althoff, Noah A. Smith, Luke Zettlemoyer
New ELMs are learned by branching from (mixtures of) ELMs in the current set, further training the parameters on data for the new domain, and then merging the resulting model back into the set for future use.
no code implementations • 26 May 2022 • Mike A. Merrill, Tim Althoff
Here, we introduce a neural architecture for multivariate time series classification designed to address these unique domain challenges.
no code implementations • 28 Mar 2022 • ASHISH SHARMA, Inna W. Lin, Adam S. Miner, David C. Atkins, Tim Althoff
Advances in artificial intelligence (AI) are enabling systems that augment and collaborate with humans to perform simple, mechanistic tasks like scheduling meetings and grammar-checking text.
no code implementations • 9 Jul 2021 • Mike A. Merrill, Tim Althoff
This architecture combines benefits from CNN and Trans-former architectures to (1) enable better prediction performance by learning directly from raw minute-level sensor data without the need for handcrafted features by up to 0. 33 ROC AUC, and (2) use pretraining to outperform simpler neural models and boosted decision trees with data from as few a dozen participants.
1 code implementation • 19 Jan 2021 • ASHISH SHARMA, Inna W. Lin, Adam S. Miner, David C. Atkins, Tim Althoff
Learning such transformations is challenging and requires a deep understanding of empathy while maintaining conversation quality through text fluency and specificity to the conversational context.
no code implementations • 21 Sep 2020 • Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan Rossi, Tim Althoff
Across 648 experiments and two datasets, we evaluate every commonly used causal inference method and identify their strengths and weaknesses to inform social media researchers seeking to use such methods, and guide future improvements.
2 code implementations • EMNLP 2020 • Ashish Sharma, Adam S. Miner, David C. Atkins, Tim Althoff
We develop a novel unifying theoretically-grounded framework for characterizing the communication of empathy in text-based conversations.
no code implementations • 28 Aug 2020 • Ge Zhang, Mike A. Merrill, Yang Liu, Jeffrey Heer, Tim Althoff
Large scale analysis of source code, and in particular scientific source code, holds the promise of better understanding the data science process, identifying analytical best practices, and providing insights to the builders of scientific toolkits.
no code implementations • 17 Aug 2020 • Jina Suh, Eric Horvitz, Ryen W. White, Tim Althoff
Most work to date on mitigating the COVID-19 pandemic is focused urgently on biomedicine and epidemiology.
1 code implementation • 10 Jul 2020 • Yang Liu, Alex Kale, Tim Althoff, Jeffrey Heer
Multiverse analysis is an approach to data analysis in which all "reasonable" analytic decisions are evaluated in parallel and interpreted collectively, in order to foster robustness and transparency.
Human-Computer Interaction
no code implementations • 19 May 2020 • David Wadden, Tal August, Qisheng Li, Tim Althoff
We found that participation in group mental health discussions led to improvements in psychological perspective, and that these improvements were larger in moderated conversations.
no code implementations • 4 Dec 2018 • Haraldur T. Hallgrímsson, Filip Jankovic, Tim Althoff, Luca Foschini
We consider the problem of modeling cardiovascular responses to physical activity and sleep changes captured by wearable sensors in free living conditions.
no code implementations • TACL 2016 • Tim Althoff, Kevin Clark, Jure Leskovec
Mental illness is one of the most pressing public health issues of our time.
no code implementations • 28 May 2014 • Tim Althoff, Hyun Oh Song, Trevor Darrell
While low-level image features have proven to be effective representations for visual recognition tasks such as object recognition and scene classification, they are inadequate to capture complex semantic meaning required to solve high-level visual tasks such as multimedia event detection and recognition.
no code implementations • 13 May 2014 • Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky
We present a case study of altruistic requests in an online community where all requests ask for the very same contribution and do not offer anything tangible in return, allowing us to disentangle what is requested from textual and social factors.