Team Opts to Continue Training Existing LLMs
boknilev · x · 2026-07-04
Drawing on experiences from other multimodal models, the team ultimately chose the second route: continuing to train an existing LLM. Due to limited resources, they couldn't run full A/B tests. The author looks forward to seeing alternative approaches and notes that new methods have already emerged while writing their paper.
More from Research
- NUS builds a soft force sensor that drives actuators without electronics or power — CurieuxExplorer · 2026-07-27
- Chelsea Finn says robot RL is bottlenecked by physical rollout cost, not algorithms — ycombinator · 2026-07-27
- ICML 2026 oral paper replication scores stay middling after a stricter re-scoring — profjamesevans · 2026-07-27
- Long-running agents will need immutable event logs, this thread argues — sebpaquet · 2026-07-27
- Seed IQ navigates Doom II, prompting questions about benchmarks beyond ARC-AGI — Fit_Transition8824 · 2026-07-27
- Agentic Data Science in Practice: Agents Write Code but Answer Wrong Questions — hugobowne · 2026-07-27