I Can’t Believe It’s Not Better Initiative
@icbinb.bsky.social
The ICBINB initiative is a movement within the ML community for well-executed meaningful research beyond bold numbers. The goals of the initiative are to crack open the research process, to re-value unexpected negative results.
icbinb.cc
icbinb.cc
(6/n) Yutaro Yamada (Sakana AI) will present “The AI Scientist-v2” — an agentic system that wrote & submitted papers to our workshop. What does this mean for peer review, novelty, and research norms?
April 22, 2025 at 8:35 PM
(6/n) Yutaro Yamada (Sakana AI) will present “The AI Scientist-v2” — an agentic system that wrote & submitted papers to our workshop. What does this mean for peer review, novelty, and research norms?
(5/n) Roberta Raileanu (Meta) will talk about using LLMs to automate scientific discovery—how far are we really? She’ll introduce MLGym & show why real-world AI research is still far from solved.
April 22, 2025 at 8:35 PM
(5/n) Roberta Raileanu (Meta) will talk about using LLMs to automate scientific discovery—how far are we really? She’ll introduce MLGym & show why real-world AI research is still far from solved.
(4/n) John Kalantari (YRIKKA / Univ. of Minnesota) will tackle the myth of generalizability in DL—why context isn’t a footnote, but the key to real-world impact. Especially in high-stakes fields like healthcare.
April 22, 2025 at 8:35 PM
(4/n) John Kalantari (YRIKKA / Univ. of Minnesota) will tackle the myth of generalizability in DL—why context isn’t a footnote, but the key to real-world impact. Especially in high-stakes fields like healthcare.
(3/n) Otilia Stretcu (Google Research) will unpack why classification still breaks in the real world—and how LLMs might help (or not). From safety to niche data, it’s messier than the benchmarks suggest.
April 22, 2025 at 8:35 PM
(3/n) Otilia Stretcu (Google Research) will unpack why classification still breaks in the real world—and how LLMs might help (or not). From safety to niche data, it’s messier than the benchmarks suggest.
(2/n) Nick Haber (Stanford) will explore where reasoning-capable LLMs still fall short — and what that means for learning, education, and human-AI collaboration.
April 22, 2025 at 8:35 PM
(2/n) Nick Haber (Stanford) will explore where reasoning-capable LLMs still fall short — and what that means for learning, education, and human-AI collaboration.
Please help spread the word. Our flyer:
December 17, 2024 at 9:11 PM
Please help spread the word. Our flyer: