7 citations · 11 across the 13 of their papers we have counts for
18 papers
Atlas: Making Sense of Long Horizon Agent Trajectories
Sangho Suh, Joseph Chee Chang, Pao Siangliulue +5
AI agents can now search literature, generate hypotheses, analyze datasets, and run experiments at a scale difficult for researchers to match. Yet scaling scientific execution does…
Sparse Feature Policy Unlearning Mitigates State Hallucination in Vision-Language-Action Models
Jiho Lee, Jeongeun Park, Heayoun Choi +2
Vision-Language-Action (VLA) models have shown strong generalization in robotic manipulation by leveraging rich representations from pretrained vision-language models. However, the…
Asterism: Exploring and Synthesizing Scattered Observations into Literature-Grounded Hypotheses and Theories
Joseph Chee Chang, Michael D'Arcy, Amy X. Zhang +15
A theory draws many independent observations into one framework with novel hypotheses. A researcher building such a theory must synthesize observations scattered across many papers…
Old Ideas, Novel Problems: The Instability of LLM-Based Novelty Evaluation
Noy Sternlicht, Simra Shahid, Peter Jansen +3
AI-based ideation systems are often evaluated on the novelty of their ideas, and that judgment is increasingly delegated to large language models. Such judges are typically built a…
Artificial Intelligence Index Report 2026
Sha Sajadieh, Loredana Fattorini, Raymond Perrault +20
Welcome to the ninth edition of the AI Index report. As AI continues to advance rapidly, the question becomes whether the systems built around it can keep up. Governance frameworks…
Omakase: proactive assistance with actionable suggestions for evolving scientific research projects
Pao Siangliulue, Jonathan Bragg, Doug Downey +2
As AI agents become increasingly capable of complex knowledge tasks, the lack of context limits their capability to proactively reason about a user's latent needs throughout a long…
Deep Research, Shallow Evaluation: A Case Study in Meta-Evaluation for Long-Form QA Benchmarks
Jena D. Hwang, Varsha Kishore, Amanpreet Singh +9
Recent advances have made long-form report-generating systems widely available. This has prompted evaluation frameworks that use LLM-as-judge protocols and claim verification, alon…
PreScience: A Dataset and Benchmark for Scientific Forecasting
Anirudh Ajith, Amanpreet Singh, Jay DeYoung +7
Can AI systems trained on the existing scientific record forecast the advances that will follow? We introduce PreScience, a dataset and benchmark for scientific forecasting built a…
Generating Literature-Driven Scientific Theories at Scale
Peter Jansen, Peter Clark, Doug Downey +1
Contemporary automated scientific discovery has focused on agents for generating scientific experiments, while systems that perform higher-level scientific activities such as theor…
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
Jonathan Bragg, Mike D'Arcy, Nishant Balepur +36
AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new directions o…
Literature-Grounded Novelty Assessment of Scientific Ideas
Simra Shahid, Marissa Radensky, Raymond Fok +3
Automated scientific idea generation systems have made remarkable progress, yet the automatic evaluation of idea novelty remains a critical and underexplored challenge. Manual eval…
Facets, Taxonomies, and Syntheses: Navigating Structured Representations in LLM-Assisted Literature Review
Raymond Fok, Joseph Chee Chang, Marissa Radensky +4
Comprehensive literature review requires synthesizing vast amounts of research -- a labor intensive and cognitively demanding process. Most prior work focuses either on helping res…
Ai2 Scholar QA: Organized Literature Synthesis with Attribution
Amanpreet Singh, Joseph Chee Chang, Chloe Anastasiades +15
Retrieval-augmented generation is increasingly effective in answering scientific questions from literature, but many state-of-the-art systems are expensive and closed-source. We in…
CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation
Peter Jansen, Oyvind Tafjord, Marissa Radensky +6
Despite the surge of interest in autonomous scientific discovery (ASD) of software artifacts (e.g., improved ML algorithms), current ASD systems face two key limitations: (1) they…
Toward Living Narrative Reviews: An Empirical Study of the Processes and Challenges in Updating Survey Articles in Computing Research
Raymond Fok, Alexa Siu, Daniel S. Weld
Surveying prior literature to establish a foundation for new knowledge is essential for scholarly progress. However, survey articles are resource-intensive and challenging to creat…
Cocoa: Co-Planning and Co-Execution with AI Agents
K. J. Kevin Feng, Kevin Pu, Matt Latzke +6
As AI agents take on increasingly long-running tasks involving sophisticated planning and execution, there is a corresponding need for novel interaction designs that enable deeper…
Challenges in Human-Agent Communication
Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi +5
Remarkable advancements in modern generative foundation models have enabled the development of sophisticated and highly capable autonomous agents that can observe their environment…
ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models
Benjamin Newman, Yoonjoo Lee, Aakanksha Naik +6
When conducting literature reviews, scientists often create literature review tables - tables whose rows are publications and whose columns constitute a schema, a set of aspects us…