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Paper Citation Record · LEDGER

Reachability Weighted Offline Goal-conditioned Resampling

As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.02577.

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

pith.paper-citation-record.v1
2506.02577 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:24:59.912161Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

14 of 14 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9821e9c-0035-4add-92d2-8b0841445205 · outbound

This paper cites AlgaeDICE: Policy Gradient from Arbitrary Experience.

Reachability Weighted Offline Goal-conditioned Resampling AlgaeDICE: Policy Gradient from Arbitrary Experience

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.457411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.457411Z digest=sha256:9f7bf70ea0bfe70efe6aed2faaa757406615ee1e9d1bdaabb0473f46876fc06d

Observation 70231539-425d-4ded-afd6-812f326a3250 · outbound

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

Reachability Weighted Offline Goal-conditioned Resampling Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.512012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.512012Z digest=sha256:a9512e70f00949b09fceea5dfb03456f59cc726ddaf5584f33644c3a5b7a2c54

Observation ed79dc79-5a62-4f48-a1cf-723761b15eaa · outbound

This paper cites GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models.

Reachability Weighted Offline Goal-conditioned Resampling GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.745260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.745260Z digest=sha256:9776bea54c3515db50421c0e1ae80db11ab129400395a6193609f742565f20fa

Observation e4597fd0-d8a6-4bf8-9af6-2792551268ac · outbound

This paper cites Contrastive difference predictive coding.

Reachability Weighted Offline Goal-conditioned Resampling Contrastive difference predictive coding

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.912161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.912161Z digest=sha256:debe268011cca48315a06f4c6aa2d7f271312177b2a38280816e5eb002dda294

Observation bd193dd9-e705-4492-b848-f8bb6d6216f2 · outbound

This paper cites C-Learning: Learning to Achieve Goals via Recursive Classification.

Reachability Weighted Offline Goal-conditioned Resampling C-Learning: Learning to Achieve Goals via Recursive Classification

Reference 2008

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.107111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.107111Z digest=sha256:73b2f07bacdcdcb62a48d91c0a63ff6e0a4b1f14e82a8943b9bcc3a7635ce05c

Observation 4a2c8f4e-4cca-4368-ae4b-bbeafb4a438c · outbound

This paper cites Charles Elkan and Keith Noto.

Reachability Weighted Offline Goal-conditioned Resampling Charles Elkan and Keith Noto

Reference 2014

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:25:00.586978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:24:59.044765Z digest=sha256:d00ee173dc932890af5051e7572861f2385496ece1a2919c850039117e5b3d8d

Observation 70300d74-6b40-4983-932a-2c0b16915638 · outbound

This paper cites Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.

Reachability Weighted Offline Goal-conditioned Resampling Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.006613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.006613Z digest=sha256:302ec172178bf3be51bdc1735a147c74bbc9de4241f37a231528b2bf4c69bfed

Observation 5054200b-91b8-4a5c-ba16-086516345e00 · outbound

This paper cites Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian.

Reachability Weighted Offline Goal-conditioned Resampling Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.657584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.657584Z digest=sha256:62bf3a9677e5b3a64c5da85aafb59a0eb238adeb240dca5bd6a45a8465200e06

Observation 4bab6db8-93d1-449a-8602-98ad5fc15346 · outbound

This paper cites Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research.

Reachability Weighted Offline Goal-conditioned Resampling Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.589610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.589610Z digest=sha256:b0af0d35ad714fa1b4c75f542dcf509164692b4a3c3fccd8d2c765860b138625

Observation 61bed893-79e2-4f54-a38c-6e486d73ed24 · outbound

This paper cites Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL.

Reachability Weighted Offline Goal-conditioned Resampling Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.838130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.838130Z digest=sha256:433983e0684bdb1aa6de55973868edc2393ec9b3890b52b9786a24c673d4ed34

Observation 5430f879-9cc5-415c-a712-75801213e893 · outbound

This paper cites Q-WSL: Optimizing Goal-Conditioned RL with Weighted Supervised Learning via Dynamic Programming.

Reachability Weighted Offline Goal-conditioned Resampling Q-WSL: Optimizing Goal-Conditioned RL with Weighted Supervised Learning via Dynamic Programming

Reference 2021

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:25:00.304005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:24:59.239998Z digest=sha256:de2213100d4b3d50c2b5791a964b6f876f3fb71bb0f5f7ad35f41ce2691b5ecc

Observation c5d1b977-6ba4-481b-a841-4a852e7a9bbc · outbound

This paper cites Goal-Conditioned Reinforcement Learning: Problems and Solutions.

Reachability Weighted Offline Goal-conditioned Resampling Goal-Conditioned Reinforcement Learning: Problems and Solutions

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.397642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.397642Z digest=sha256:3040e5527220f991719701e9f8786bc581425de52c4eacbcdfb02d9d3e5047be

Observation 431af040-bbdf-4ca6-a6d0-43b31425a43f · outbound

This paper cites Goal-Conditioned Data Augmentation for Offline Reinforcement Learning.

Reachability Weighted Offline Goal-conditioned Resampling Goal-Conditioned Data Augmentation for Offline Reinforcement Learning

Reference 2023

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:25:00.491537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:24:59.175627Z digest=sha256:62c61ecca40d15938d915534c5ba982a58973f4adc0a1e0a4e56836950ce62a9

Observation 8d910177-1e81-4cff-acaf-decefdb1575f · outbound

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

Reachability Weighted Offline Goal-conditioned Resampling Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T11:24:59.326200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:24:59.326200Z digest=sha256:d73906faeb714a29abf88437040b05fcd0810308cdb2ca0ad2b060127acf42a4

Pith citing papers

No inbound Pith citation observations are available.