Paper Citation Record · LEDGER

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning

As of 12 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.07769.

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

pith.paper-citation-record.v1
2507.07769 v3

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:36:13.335046Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

23 of 23 outbound references displayed

verified exact0
verified fuzzy19
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e2880171-3ab1-4877-8316-94f1118f9b33 · outbound

This paper cites write newline.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:11.862425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09acc911-2842-4439-8733-f42a542709fc · outbound

This paper cites Using dimensionality reduction to exploit constraints in reinforcement learning.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Using dimensionality reduction to exploit constraints in reinforcement learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:16.834354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 332e8486-5d8f-442a-b27d-cd1fe1196164 · outbound

This paper cites Learning action representations for reinforcement learning.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Learning action representations for reinforcement learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:16.695821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8cfd6854-8973-479b-a1ca-cb726c07060d · outbound

This paper cites B., Lawrie, L.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning B., Lawrie, L

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:16.496432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 24761ec9-8dfb-4c9e-8e72-b5ab203188cd · outbound

This paper cites and Chen, Q.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning and Chen, Q

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:16.311689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e61b0259-8353-4980-8074-05b2ce34cb4f · outbound

This paper cites Us department of energy commercial reference building models of the national building stock.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Us department of energy commercial reference building models of the national building stock

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:16.105339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4d2210d7-dc5f-43a7-8ff8-2c767f322682 · outbound

This paper cites Cross temporal-spatial transferability investigation of deep reinforcement learning control strategy in the building hvac system level.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Cross temporal-spatial transferability investigation of deep reinforcement learning control strategy in the building hvac system level

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:15.950970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3796c1f3-1f3f-4f9c-8977-c1fe4a1202cb · outbound

This paper cites The Smart Buildings Control Suite: A Diverse Open Source Benchmark to Evaluate and Scale HVAC Control Policies for Sustainability.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning The Smart Buildings Control Suite: A Diverse Open Source Benchmark to Evaluate and Scale HVAC Control Policies for Sustainability

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:12.260140Z

Source-reported events for the cited work

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Observation 7e338b9b-3b6a-4612-9ba7-8a4b83a84c62 · outbound

This paper cites an unresolved cited work.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:36:15.777801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fbe5da35-16c8-485c-a3d6-5d56ab7e2f2e · outbound

This paper cites Efficient discovery of pareto front for multi-objective reinforcement learning.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Efficient discovery of pareto front for multi-objective reinforcement learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:15.598425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 71213e5d-931a-4b88-be4b-c37306ddefc2 · outbound

This paper cites Predictive control for energy efficient buildings with thermal storage: Modeling, stimulation, and experiments.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Predictive control for energy efficient buildings with thermal storage: Modeling, stimulation, and experiments

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:15.451131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 574cc0d7-b1c0-4d5d-8c32-733838c4d622 · outbound

This paper cites The citylearn challenge 2022: Overview, results, and lessons learned.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning The citylearn challenge 2022: Overview, results, and lessons learned

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:15.289449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 02cb8dd7-6355-4702-b030-903394be36f6 · outbound

This paper cites Rewarded soups: towards pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Rewarded soups: towards pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:15.121549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5d9f325c-bfc5-4e58-9f8b-819b7e8eb0b6 · outbound

This paper cites Multi-task reinforcement learning with context-based representations.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Multi-task reinforcement learning with context-based representations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:12.637945Z

Source-reported events for the cited work

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Observation d0cbf9f2-c5e5-4f35-a785-279dc2b7725c · outbound

This paper cites M., Quan, J., Kirkpatrick, J., Hadsell, R., Heess, N., and Pascanu, R.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning M., Quan, J., Kirkpatrick, J., Hadsell, R., Heess, N., and Pascanu, R

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:14.908393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8947f91b-404a-46fe-8d93-f5553c467199 · outbound

This paper cites On generalization across environments in multi-objective reinforcement learning.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning On generalization across environments in multi-objective reinforcement learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:14.745639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 195cf371-0783-4259-a98b-09f921ed8b65 · outbound

This paper cites A multi-objective home energy management system based on internet of things and optimization algorithms.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning A multi-objective home energy management system based on internet of things and optimization algorithms

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:14.597813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8080af4b-af12-455c-86b2-e5e888d62eba · outbound

This paper cites S., and Pang, X.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning S., and Pang, X

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:14.421172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b849946b-8d6a-46b5-839a-caa312e42903 · outbound

This paper cites One for many: Transfer learning for building hvac control.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning One for many: Transfer learning for building hvac control

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:14.221959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 187809e8-0078-40a4-a280-7ab5e4319edd · outbound

This paper cites A generalized algorithm for multi-objective reinforcement learning and policy adaptation.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning A generalized algorithm for multi-objective reinforcement learning and policy adaptation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:14.071847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9cf3ac7b-4688-4458-89ca-9249904bca01 · outbound

This paper cites A review of deep reinforcement learning for smart building energy management.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning A review of deep reinforcement learning for smart building energy management

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:13.897647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4c05aa4e-ee06-4cad-965e-52d68b3be1b3 · outbound

This paper cites Bear: Physics-principled building environment for control and reinforcement learning.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning Bear: Physics-principled building environment for control and reinforcement learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:13.749228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dccbc056-a223-418e-a555-101906c4ca90 · outbound

This paper cites J., Graf, P., and Jiang, H.

BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning J., Graf, P., and Jiang, H

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:13.574074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.