9/9 CT Open asks a broader AI question:
Can models forecast when the answer is not yet public -- rather than already sitting in a benchmark or on the web?
Fall Open 2026 is live. Any method is welcome.
๐ https://t.co/38xNTVWnOS
See you at @COLM_conf in SF! ๐
8/9 Early results expose a real capability gap:
Simple LM and neural baselines remain competitive with -- and sometimes beat -- strong LLMs. RAG helps inconsistently. Web agents find useful evidence, but are costly and double-edged.
True forecasting remains far from solved.
@haider1 Our paper, at COLM 2025 as Oral Spotlight, pointed directly to this direction, where we used a light-weight state-space model to retrieve important information for a downstream LLM to answer a question about extremely long documents!
Check out our paper: https://t.co/QmJtS1DO1y.