---
status: accepted
date: 2026-05-30
deciders: [Codeseys, ARIA]
builds-on: [ADR-006 (RL frameworks), ADR-007 (distillation menu), ADR-008 (Dr.GRPO base)]
---

# ADR-014: Policy-optimization objective MENU — make RL's base objective selectable

## Context and Problem Statement

The framework replicates Composer 2.5's recipe as **base RL objective + distillation
channel + preference channel**. ADR-007 already gave the *distillation/preference*
axis a menu (SimPO / TAID / Entropy-Aware-OPD via `compose_loss(dpo_variant=,
sdpo_wrapper=)`). But the **base policy-optimization objective was hardcoded to
Dr.GRPO** via `make_dr_grpo_config` — `loss_type="dr_grpo"`, `scale_rewards="none"`,
`num_iterations=1`, no other options.

User ask (2026-05-30): *"look at other policy optimization papers like SDPO and
Dr.GRPO or OPSD ... allow for RL to have multiple options ... [SDPO / what Composer
2.5 uses] is one of the best instances of setting up post-training to take models to
massive performance gains."*

So: give the base RL objective a real menu, grounded in the current PO frontier and
in what Composer 2.5 actually does.

## Research (primary-sourced, 2026-05-30)

Three parallel cross-family research passes (reports in `docs/research/`):

1. **Composer 2.5's actual recipe** (cursor.com/blog/composer-2-5 + Composer 2 report
   arXiv:2603.24477): base objective is **Dr.GRPO** (no length-std normalization,
   single-epoch, k1-discussed/k3-in-TRL KL, async RL with MoE router replay). Its
   headline 2.5 technique — "targeted RL with textual feedback" — is **on-policy
   self-distillation** (= our SDPO channel ✓). **No DPO / preference pairs / multiple
   teachers appear in any Composer source** — our trace-replay-DPO channel is the
   framework's own addition, NOT Composer's. Recorded honestly.

2. **GRPO-family PO landscape**: vanilla GRPO (2402.03300), Dr.GRPO (2503.20783),
   DAPO (2503.14476, decoupled clip-higher + dynamic sampling + KL-off), GSPO
   (2507.18071, sequence-level importance ratio — Qwen3, MoE-stable), CISPO
   (MiniMax-M1 2506.13585, detached-IS REINFORCE so every token keeps a gradient),
   GMPO (geometric-mean aggregation). Most are surgical edits to advantage-norm /
   length-norm / clip / ratio-granularity / KL.

3. **TRL 1.5.0 capability map** — then **verified by introspecting the installed
   package** (not a GitHub snapshot): the installed trl 1.5.0 `GRPOTrainer` already
   implements `loss_type ∈ {grpo, dr_grpo, bnpo, dapo, cispo, luspo, sapo, vespo}`
   and exposes `epsilon`/`epsilon_high` (decoupled clip), `delta`, `beta`,
   `scale_rewards ∈ {group,batch,none}`, `importance_sampling_level ∈ {token,
   sequence}` (= GSPO), `mask_truncated_completions`, `num_iterations`. **Every
   objective we want is therefore PURE CONFIG — no custom `_compute_loss` needed.**

## Decision

Add **`make_po_config(objective=..., **overrides)`** to `trainer/composer_trainer.py`
— a named-preset factory over trl 1.5.0's verified GRPOConfig knob-space. Keep
`make_dr_grpo_config` intact (back-compat); `dr_grpo` is now one preset among the menu.

Menu (`PO_OBJECTIVES`):

| objective | loss_type | key knobs | what it gives |
|---|---|---|---|
| `grpo` | grpo | scale_rewards=group, IS=token | vanilla GRPO (std-norm advantage) |
| `dr_grpo` | dr_grpo | scale_rewards=none, IS=token | **default**; no length-std bias (Composer 2.5 base) |
| `bnpo` | bnpo | scale_rewards=batch | batch-normalized variant |
| `dapo` | dapo | epsilon_high=0.28, mask_truncated, beta=0 | decoupled clip-higher, anti-entropy-collapse |
| `gspo` | grpo | IS=**sequence** | sequence-level ratio; long-CoT / MoE stable (Qwen3) |
| `cispo` | cispo | epsilon_high=5.0 | detached-IS REINFORCE; every token keeps gradient |

Each preset carries literature-recommended settings; any field is overridable via
`**overrides`. **Drift guards** assert the requested `loss_type` /
`importance_sampling_level` / `epsilon_high` actually applied, so a preset can never
silently degrade (e.g. GSPO with `importance_sampling_level` overridden back to token
raises rather than quietly becoming GRPO).

### Consequences

- **Positive**: RL now has 6 selectable base objectives at zero custom-loss cost; the
  ladder/runners gain an `objective=` knob orthogonal to the existing SDPO/replay
  channels and the SimPO/TAID/EA-OPD distillation menu. A user can run e.g.
  `objective="dapo"` (clip-higher) or `objective="gspo"` (MoE-stable) instead of only
  Dr.GRPO.
- **Positive**: faithful to Composer 2.5 (dr_grpo default + self-distillation) while
  exposing the stronger 2025-26 objectives the report predates.
- **Neutral**: `gspo` is `grpo` loss + `importance_sampling_level="sequence"` (trl has
  no literal "gspo"); documented in the preset + guarded.
- **Negative / honest**: presets reflect *current* trl 1.5.0 field names; a trl upgrade
  could rename knobs — the drift guards turn that into a loud failure, not silent
  mis-training. `sapo`/`luspo`/`vespo` exist in this trl build but are NOT in the menu
  yet (less-established; add later if validated).

## Acceptance gate

- [x] `make_po_config(objective)` with presets grpo/dr_grpo/bnpo/dapo/gspo/cispo,
  built over trl-1.5.0-verified knobs (introspected, not assumed).
- [x] `make_dr_grpo_config` preserved; `dr_grpo` preset is equivalent; default objective
  is `dr_grpo`.
- [x] Unit tests (10) green against real trl 1.5.0: each preset's defining knob asserted,
  unknown-objective raises with the menu, GSPO token-override guard fires, overrides apply.
- [x] Drift guards on loss_type / IS-level / epsilon_high.
- [ ] Wire `objective=` through the LMA ladder runners (follow-up; the A1 run used
  dr_grpo — re-runnable with `objective="dapo"` etc. once threaded).

## More Information

- `docs/research/SELF_DISTILLATION_LANDSCAPE.md` — the distillation/preference menu (ADR-007).
- Composer 2.5 recipe report + GRPO-family survey + trl-1.5.0 capability map: research
  pass 2026-05-30 (parallel cross-family).
- Installed-trl introspection confirming the knob surface: 2026-05-30.