Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T16:27:59.369199Z
Paper Citation Record · LEDGER
As of 4 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.18006.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T16:27:59.369199Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
35 of 35 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 1f11a536-74f8-4725-aecc-df04d89b869c · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Training language models to reason efficiently , url =
Reference 1
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Observation e879c3e6-9204-4e84-8e3a-e9153cfd1c97 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 2
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Observation 2537a7cf-e35f-4445-baef-594c86e7bbef · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models An empirical study on eliciting and improving
Reference 3
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Observation aa65e37e-90d0-4960-bce0-c2a44cb976bd · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Christiano and Jan Leike and Tom B
Reference 4
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Observation ee983df6-3c37-411f-8685-9488804ea4f2 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Process reinforcement through implicit rewards , url =
Reference 5
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Observation 53b21f1a-c083-4c01-9aa9-bd0c14aaca8f · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Reinforcement learning for reasoning in small
Reference 6
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Observation 39fc7620-3b95-40d1-8514-9197a9bc0d27 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 7
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Observation c0b6a909-68f7-4f7f-a4bf-6a40bba1ed7e · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Tenenbaum and Igor Mordatch , journal =
Reference 8
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Observation 9a08082a-1d71-435d-b5b7-7bbdd4f70fac · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Rae and Laurent Sifre , journal =
Reference 9
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Observation 3fe24059-8875-4d9a-8597-c13ca83c4bf6 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Lu Wang and Weizhu Chen , journal =
Reference 10
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Observation e268f8d0-5925-4ee2-8167-70bd29029657 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Aligning language models with offline learning from human feedback , url =
Reference 11
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Observation 202b353d-1000-4bf1-b2a5-d6aa9583e2fb · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 12
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Observation 99abe00c-f04c-4391-9b7f-8baba8c55339 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 13
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Observation d346f2a6-2c46-485a-8bae-4b4b6ecd79c2 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Encouraging divergent thinking in large language models through multi-agent debate , url =
Reference 14
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Observation 789a0f5d-c0dd-4837-a158-1c208722b1c5 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 15
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Observation 681c953c-df0d-48af-8e5e-d81c6268cded · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Let's verify step by step , url =
Reference 16
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Observation b7b58bcd-32d2-4ae1-8b72-bac85c1fd75a · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 17
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Observation 8d583203-0413-43ad-90bf-bc7f55f3baf8 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Decoupled weight decay regularization , url =
Reference 18
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Observation db91a171-d5ef-44c3-8d85-b9c703139881 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Tang and Manan Roongta and Colin Cai and Jeffrey Luo and Li Erran Li and Raluca Ada Popa and Ion Stoica , note =
Reference 19
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Observation 661d5186-70ea-4bd4-b432-869bd540527d · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 20
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Observation c518ff40-7516-4c96-9051-46ee4fd284c9 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 21
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Observation deaed43f-98b8-4a3f-9a69-5dc13f9cc25f · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 22
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Observation 1e02256b-6be4-48c7-a571-151db92e06ee · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 23
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Observation e4ae42e5-d29d-4bed-8c53-30aa88025b15 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 24
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Observation 1be8d935-5523-4508-9678-d1c292aa7113 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 25
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Observation 20557ec1-8d05-425a-91e8-17c0fd7219c6 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Tenenbaum and Antonio Torralba and Shuang Li and Igor Mordatch , journal =
Reference 26
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Observation 1db38d7b-e75b-4524-85dd-aef9b38528a9 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Offline Reinforcement Learning for
Reference 27
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Observation 146ef1e4-0700-4636-a7d6-274c49a32241 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Tina: Tiny reasoning models via
Reference 28
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Observation 3b57f0a6-b9fe-4f06-a3e7-d2082c230624 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Le and Ed H
Reference 29
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Observation 3d919d21-9b24-4900-a6ed-ab7eeb8ecfb1 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Chain-of-thought prompting elicits reasoning in large language models , url =
Reference 30
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Observation 3a0a30a4-3ebd-4b1d-b273-55298ba667df · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Towards large reasoning models: A survey of reinforced reasoning with large language models , url =
Reference 31
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Observation 8c7e0609-fc24-44d9-8922-c7190dd919bb · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Griffiths and Yuan Cao and Karthik Narasimhan , journal =
Reference 32
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Observation 2a060402-f705-4c0f-9927-df78b2e64e89 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 33
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Observation 249b5484-1bd8-4b5b-82b3-d547fac87604 · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models What's behind
Reference 34
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Observation 7fccc60f-d235-469d-a747-7396aedca89a · outbound
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models Unresolved cited work
Reference 35
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No inbound Pith citation observations are available.