Joined September 2015
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Gabrielle Kaili-May Liu (Kaili) ✈️ COLM retweeted
Given a request, AI systems generate long-form reports. Report evaluation relies on nuggets: essential & granular facts. Prior work on nugget generation treats them as short statements. Our #ICTIR2026 oral proposes DoGMaTiQ, an automated pipeline for Q&A nuggets.
1/6🧵
Gabrielle Kaili-May Liu (Kaili) ✈️ COLM retweeted
🔥 New paper alert!! Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents? 🔥
We increasingly trust LLM judges to supervise deep research agents. But can we trust the judges themselves? Turns out: even frontier models score below 50% 😯
Details 🧵👇
Gabrielle Kaili-May Liu (Kaili) ✈️ COLM retweeted
When multimodal AI meets real-world expertise, reasoning gets harder, deeper, and much more exciting.
Join us at KnowledgeMR @ #CVPR2026 to push this frontier forward!
🗓️Thu June 4 | 8am | Room 704/706
Speakers: @thoma_gu @huang_biwei @pliang279 @MengdiWang10 @xwang_lk
Gabrielle Kaili-May Liu (Kaili) ✈️ COLM retweeted
1/9 🚀 New paper: Demystifying Scientific Problem-Solving in LLMs — How does reasoning enhancement affect knowledge recall, and do LLMs benefit from external knowledge complimentary to reasoning?
Tldr;
📊 SciReas: holistic and efficient evaluation suite for scientific reasoning
🧠 KRUX: a novel framework to study knowledge vs reasoning in LLMs
🔑 Findings: knowledge is a bottleneck; reasoners + in-context knowledge help; long CoT helps knowledge recall/utilization
Gabrielle Kaili-May Liu (Kaili) ✈️ COLM retweeted
Excited to see more investigation into LLM creativity. We have some pioneering work on this topic as well:
Creativity or Brute Force?
Using Brainteasers as a Window into the
Problem-Solving Abilities of Large Language Models. arxiv.org/pdf/2505.10844.
