R0041/2026-04-01/Q003/SRC03/E01¶
RLVR fundamental limitations for open-ended and subjective tasks
URL: https://arxiv.org/html/2511.02463v3
Extract¶
RLVR's "success has been largely confined to the mathematical and programming domains with clear and automatically checkable outcomes, while it struggles with open-ended tasks like creative writing and subjective Q&A where no unambiguous ground truth exists."
"Since RLVR fundamentally relies on verifiers that presuppose the existence of standard answers, it cannot be directly applied to open-ended tasks."
Additional finding: "RLVR is known for degrading generation diversity, which causes [models] to fall short on subjective reasoning that has multiple answers depending on different role perspectives."
Research into extending RLVR to open-ended tasks via multiple-choice reformulation shows promise but requires reformulating open questions into verifiable formats, which may lose nuance.
Anti-sycophancy filter research found indicators of reward hacking including "prefatory sycophancy (gratuitous praise of the user's prompt) and laudatory self-evaluation (meta-commentary on the response's own merit)."
Relevance to Hypotheses¶
| Hypothesis | Relationship | Strength |
|---|---|---|
| H1 | Contradicts | RLVR "cannot be directly applied to open-ended tasks" |
| H2 | Supports | Confirms domain limitations while noting active research to extend |
| H3 | Supports | Diversity degradation could worsen homogenization-related sycophancy |
Context¶
The diversity degradation finding is particularly relevant: if RLVR reduces the range of model outputs, it could paradoxically increase a form of sycophancy by reducing the model's ability to generate diverse, challenging perspectives.