Paper Citation Record · LEDGER

Adaptive Policy Backbone via Shared Network

As of 18 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2509.22310.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.22310 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:49:59.794278Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact1
verified fuzzy3
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

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Outbound references

Observation 6a9ca6ba-bd01-49f2-80b8-778104f2140b · outbound

This paper cites degenerate.

Adaptive Policy Backbone via Shared Network degenerate

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:50:00.153254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4e85b819-979a-406e-9ec7-9ea4bb07a619 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

Adaptive Policy Backbone via Shared Network On First-Order Meta-Learning Algorithms

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.695466Z

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Unavailable: canonical work link unavailable.

Observation 1deb65c4-9b8e-40c6-8485-f3d51ecd5df9 · outbound

This paper cites Solving Rubik's Cube with a Robot Hand.

Adaptive Policy Backbone via Shared Network Solving Rubik's Cube with a Robot Hand

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.711210Z

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Observation b28df3d7-f8de-4139-9a13-3594f750127c · outbound

This paper cites Behavior Regularized Offline Reinforcement Learning.

Adaptive Policy Backbone via Shared Network Behavior Regularized Offline Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.718704Z

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Observation 1ceecf3a-9e06-4f0c-85de-24865542deba · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Adaptive Policy Backbone via Shared Network Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.722543Z

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Observation 3a83e20b-e3e1-4619-b4f5-4167e284c1ce · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Adaptive Policy Backbone via Shared Network Offline Reinforcement Learning with Implicit Q-Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.726441Z

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Observation 05c43a16-7500-433b-adfa-5bdbf776c883 · outbound

This paper cites Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML.

Adaptive Policy Backbone via Shared Network Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.730352Z

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Observation 414ac2dd-1cdd-4af4-b619-c4e96c4c8cc5 · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.

Adaptive Policy Backbone via Shared Network LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.742716Z

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Observation 292373e9-f99b-4da4-810e-9247c6fa5f60 · outbound

This paper cites BitFit: Simple parameter-efficient fine- tuning for transformer-based masked language-models.arXiv preprint arXiv:2106.10199,.

Adaptive Policy Backbone via Shared Network BitFit: Simple parameter-efficient fine- tuning for transformer-based masked language-models.arXiv preprint arXiv:2106.10199,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.746322Z

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Observation 2ac2e632-91cf-4f6d-87b4-7fadc3e7afd5 · outbound

This paper cites Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation.

Adaptive Policy Backbone via Shared Network Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.749675Z

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Observation 3086fa2c-6aa3-46e0-b15f-0a51c63f3e23 · outbound

This paper cites Universal Successor Features Approximators.

Adaptive Policy Backbone via Shared Network Universal Successor Features Approximators

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.753524Z

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Observation 741d5ac3-a158-4028-83ef-8c6e7ea260c1 · outbound

This paper cites Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning.

Adaptive Policy Backbone via Shared Network Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.757366Z

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Observation 9477da09-850c-4b91-bf38-89168baef5ea · outbound

This paper cites Some Considerations on Learning to Explore via Meta-Reinforcement Learning.

Adaptive Policy Backbone via Shared Network Some Considerations on Learning to Explore via Meta-Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.761012Z

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Observation 26847317-8382-4273-971e-fb3937ac9729 · outbound

This paper cites ES-MAML: Simple Hessian-Free Meta Learning.

Adaptive Policy Backbone via Shared Network ES-MAML: Simple Hessian-Free Meta Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.764887Z

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Observation c9e7e083-7a17-48c6-a939-29950eedd8a7 · outbound

This paper cites VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning.

Adaptive Policy Backbone via Shared Network VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.768452Z

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Observation 828391e7-c6ee-418c-8edf-340adefe9786 · outbound

This paper cites A Tutorial on Meta-Reinforcement Learning.

Adaptive Policy Backbone via Shared Network A Tutorial on Meta-Reinforcement Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.772066Z

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Observation b23d4ff5-a654-4fd2-92da-040e0ae7a8fe · outbound

This paper cites Learning to Learn: Meta-Critic Networks for Sample Efficient Learning.

Adaptive Policy Backbone via Shared Network Learning to Learn: Meta-Critic Networks for Sample Efficient Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.775920Z

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Observation 95864adc-3203-4c64-8dba-bbcdb68dde2d · outbound

This paper cites Parameter Space Noise for Exploration.

Adaptive Policy Backbone via Shared Network Parameter Space Noise for Exploration

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.783118Z

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Observation da34e2a3-9d08-40aa-b1df-f3980800a6b0 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Adaptive Policy Backbone via Shared Network Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.786714Z

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Observation ac7fa0b2-8f80-474d-90df-718b9516b643 · outbound

This paper cites In meta-test, the agent is evaluated atθ= 1.5π, that is,x= 3 cosθ,y= 3 sinθ.

Adaptive Policy Backbone via Shared Network In meta-test, the agent is evaluated atθ= 1.5π, that is,x= 3 cosθ,y= 3 sinθ

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:50:00.166748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 973ae3f2-e8bb-4640-aa38-2310ccc672c9 · outbound

This paper cites Revisit Policy Optimization in Matrix Form.

Adaptive Policy Backbone via Shared Network Revisit Policy Optimization in Matrix Form

Reference 2007

Resolution: verified exact; local_arxiv, observed 2026-08-15T15:50:00.138816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1aef2f06-c341-481c-9fe6-06b30aa21ddc · outbound

This paper cites RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning.

Adaptive Policy Backbone via Shared Network RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.703482Z

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Observation 136b4f67-5e1c-4156-9b51-c756204b629b · outbound

This paper cites A Simple Neural Attentive Meta-Learner.

Adaptive Policy Backbone via Shared Network A Simple Neural Attentive Meta-Learner

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.691118Z

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Observation 74f6ec7a-7cbf-47d2-90d4-83ad4c2c0aba · outbound

This paper cites Learning to reinforcement learn.

Adaptive Policy Backbone via Shared Network Learning to reinforcement learn

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.699119Z

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Observation 21437c3d-b1cd-4bcc-8ecb-08a9d841156a · outbound

This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

Adaptive Policy Backbone via Shared Network Dota 2 with Large Scale Deep Reinforcement Learning

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.707291Z

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Observation 01db3086-9d60-49cb-b969-5ed2172b8e29 · outbound

This paper cites Off-policy deep reinforcement learning without exploration.

Adaptive Policy Backbone via Shared Network Off-policy deep reinforcement learning without exploration

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:50:00.180795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a0314d63-cc19-4a94-818a-629cd1cd223c · outbound

This paper cites Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

Adaptive Policy Backbone via Shared Network Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.738570Z

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Observation a21779bf-7180-49c6-9252-5ea53c32fa28 · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

Adaptive Policy Backbone via Shared Network Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.734533Z

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Observation 6c9b0a5a-8041-40a8-a9c6-d9eb14e3526f · outbound

This paper cites Sharing Knowledge in Multi-Task Deep Reinforcement Learning.

Adaptive Policy Backbone via Shared Network Sharing Knowledge in Multi-Task Deep Reinforcement Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.779619Z

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Pith citing papers

No inbound Pith citation observations are available.