Scalable Chain of Thoughts via Elastic Reasoning
Large reasoning models (LRMs) have achieved remarkable progress on complex
tasks by generating extended chains of thought (CoT). However, their
uncontrolled output lengths pose significant challenges for real-world
deployment, where inference-time budgets on tokens, latency, or compute are
strictly constrained. We propose Elastic Reasoning, a novel framework for
scalable chain of thoughts that explicitly separates reasoning into two
phases--thinking and solution--with independently allocated budgets. At test
time, Elastic Reasoning prioritize that completeness of solution segments,
significantly improving reliability under tight resource constraints. To train
models that are robust to truncated thinking, we introduce a lightweight
budget-constrained rollout strategy, integrated into GRPO, which teaches the
model to reason adaptively when the thinking process is cut short and
generalizes effectively to unseen budget constraints without additional
training. Empirical results on mathematical (AIME, MATH500) and programming
(LiveCodeBench, Codeforces) benchmarks demonstrate that Elastic Reasoning
performs robustly under strict budget constraints, while incurring
significantly lower training cost than baseline methods. Remarkably, our
approach also produces more concise and efficient reasoning even in
unconstrained settings. Elastic Reasoning offers a principled and practical
solution to the pressing challenge of controllable reasoning at scale.
681d7ccb572e742b3f42d1f3
Yuhui Xu
admin_assigned
2025-05-09T08:56:04.644Z
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/avatars/c14b5953a716f42c83ad28147f8308ae.svg
Yuhui Xu
user
yuhuixu
681d7ccb572e742b3f42d1f4
Hanze Dong
admin_assigned
2025-05-09T08:56:10.829Z
63a3ff69f91ad3ea5703841d
/avatars/69227c4bce01d33747c1377b6f9672db.svg
Hanze Dong
user
hendrydong
681d7ccb572e742b3f42d1f5
Lei Wang
claimed_verified
2025-06-09T10:13:17.176Z
646def60df618b303b419323
/avatars/97aa761d5255abf230304cfeade87835.svg
Lei Wang
user
demolei
681d7ccb572e742b3f42d1f6
Doyen Sahoo
admin_assigned
2025-05-09T08:56:18.676Z
65f84fd980481173afd91233
/avatars/6ac7bd6beba24d1476c5179b88c9e3fa.svg
Doyen
user
doyensahoo
681d7ccb572e742b3f42d1f7
Junnan Li
admin_assigned
2025-05-09T08:56:32.272Z
61f9d3b54ac99e8a1bae85f4
/avatars/ac47d13204dd22452e4bc46e280842d5.svg
JunnanLi
user
JunnanLi
681d7ccb572e742b3f42d1f8
Caiming Xiong
admin_assigned
2025-05-09T08:56:38.430Z
649dbcc4e0fff1ed099dc80a
/avatars/c87c273ca628dbcddccbf1ee19b2ce33.svg
Caiming Xiong
user
cxiong
Scalable Chain of Thoughts via Elastic Reasoning
Large reasoning models (LRMs) have achieved remarkable progress on complex
tasks by generating extended chains of thought (CoT). However, their
uncontrolled output lengths pose significant challenges for real-world
deployment, where inference-time budgets on tokens, latency, or compute are
strictly constrained. We propose Elastic Reasoning, a novel framework for
scalable chain of thoughts that explicitly separates reasoning into two
phases--thinking and solution--with independently allocated budgets. At test
time, Elastic Reasoning prioritize that completeness of solution segments,
significantly improving reliability under tight resource constraints. To train
models that are robust to truncated thinking, we introduce a lightweight
budget-constrained rollout strategy, integrated into GRPO, which teaches the
model to reason adaptively when the thinking process is cut short and
generalizes effectively to unseen budget constraints without additional
training. Empirical results on mathematical (AIME, MATH500) and programming
(LiveCodeBench, Codeforces) benchmarks demonstrate that Elastic Reasoning
performs robustly under strict budget constraints, while incurring
significantly lower training cost than baseline methods. Remarkably, our
approach also produces more concise and efficient reasoning even in
unconstrained settings. Elastic Reasoning offers a principled and practical
solution to the pressing challenge of controllable reasoning at scale.
Elastic Reasoning is a framework that divides reasoning into thinking and solution phases with separate budgets, improving model reliability and efficiency under resource constraints.
Elastic Reasoning chain of thoughts GRPO budget-constrained rollout strategy