LPO
[NeurIPS 2026] Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex
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GITHUB · launched Nov 1, 2026 · 14 upvotes (top 98%) · 0 views
Niche: reinforcement learning frameworks · 72 launches, 3 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
Visit website ↗ Source listing ↗
Could you build this?
No This is novel NeurIPS-level RL research on policy optimization for LLMs, and a real version requires research-grade theory, large-scale training compute, and benchmark validation.
What it would actually take: Reproducing the work means implementing a group-based RLVR objective in a distributed training stack (PyTorch with a large-model framework), running many GPU-hours of experiments, and matching published results on reasoning benchmarks. The core contribution is a new mathematical formulation that must be derived and validated by people with ML research expertise.
Competitors
Other products that read as similar to this one : 2309 launches clear the similarity bar, closest 8 shown.
Attention rank: #2288 of 2310 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 367 days after the earliest competitor.
- KLPO · github · 2026-09-19 · 180 upvotes · similarity 0.62
- WAVE-0 · github · 2026-10-13 · 26 upvotes · similarity 0.60
- FPO · github · 2026-10-29 · 122 upvotes · similarity 0.58
- awesome-post-training-RL · github · 2026-09-11 · 11 upvotes · similarity 0.56
- survival-rl · github · 2026-09-27 · 12 upvotes · similarity 0.56
- Nested-Adversarial-Containment · github · 2026-10-07 · 13 upvotes · similarity 0.56
- LoopWAM · github · 2026-10-12 · 31 upvotes · similarity 0.55
- VaM · github · 2026-10-13 · 16 upvotes · similarity 0.54
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