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Paper Citation Record · LEDGER

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration

As of 16 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2502.02628.

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

pith.paper-citation-record.v1
2502.02628 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T12:11:21.981193Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:18:12.166532Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T17:35:48.442952Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d8dc0c14-1e56-425f-9c13-92f81bc530bc · outbound

This paper cites Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.939061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.939061Z digest=sha256:66d378cd12901115777fd9b1558affa520b72ada038ed23ab345873e69eeb13c

Observation 01e10bc9-eb54-4dab-ac59-af1746945dcc · outbound

This paper cites RLTF: Reinforcement Learning from Unit Test Feedback.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration RLTF: Reinforcement Learning from Unit Test Feedback

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.953185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.953185Z digest=sha256:a722b406eaa0754c2d9adcf2ed4f154f4e007ab8a39ce6ade70f01c486a39cf7

Observation 0c88e1cd-3f51-4a18-a712-9e3aeba6a0c8 · outbound

This paper cites Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.967541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.967541Z digest=sha256:75c27a6f81c92642af8c0563fcf637a36da9ede7c5e83629b24268e05fb3d3c3

Observation f2982919-b534-4fac-a43d-5dafaa005de9 · outbound

This paper cites Panacea: Pareto Alignment via Preference Adaptation for LLMs.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Panacea: Pareto Alignment via Preference Adaptation for LLMs

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.971938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.971938Z digest=sha256:ab0df1728f4d08215cb3e967805a5159bb9d0eaee2a95ade492d2cabb6471a5d

Observation 2adec81f-4050-46c2-a2f3-a5e07375ef07 · outbound

This paper cites Beyond one-preference-fits-all alignment: Multi-objective direct preference optimization.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Beyond one-preference-fits-all alignment: Multi-objective direct preference optimization

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T12:11:22.348870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-09T12:11:21.976508Z digest=sha256:5ac34370206aeb4a19d94c793a986fc21e2d09ac16074e4a36f95c24e09af732

Observation 5fc9c0df-dbbd-4974-b34b-d4c881f0fa24 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Fine-Tuning Language Models from Human Preferences

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.981193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.981193Z digest=sha256:82fb5bb4cdaac5ee422851df9d0c5d79d3d2449672f080fba9972dff6a54f29a

Observation 2da3be00-2b93-4b6a-80b9-b9381a31a13f · outbound

This paper cites Contrastive Preference Learning: Learning from Human Feedback without RL.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Contrastive Preference Learning: Learning from Human Feedback without RL

Reference 1971

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.943767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.943767Z digest=sha256:02732c418784620e3bdb6e798fd5ee52c93e2a28520e19546b97dc304564822c

Observation 0c78cfb3-14d7-4644-9215-f2fb06d9bb9d · outbound

This paper cites Deep Generative Model for Mechanical System Configuration Design.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Deep Generative Model for Mechanical System Configuration Design

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.929681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.929681Z digest=sha256:27081298b0defd9507ec9f88f90763f80aba5f7c191eb43154da40cfe52caf9b

Observation e37066ae-2d7d-40b8-8b8e-00bec3edcc6f · outbound

This paper cites Multi-objective Reinforcement learning from AI Feedback.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Multi-objective Reinforcement learning from AI Feedback

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.962879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.962879Z digest=sha256:7e44039ff86e3d1de46e975c95118974d3c916d613555f7cf8be81e485a7d585

Observation a4c7e8b3-628c-45ad-8771-e82d559dc8ef · outbound

This paper cites Proximal Policy Optimization Algorithms.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Proximal Policy Optimization Algorithms

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.958433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.958433Z digest=sha256:98bdaf842c167e9a0351290fbfcd0ad11355de2088773077dc856f4cb9d89773

Observation 950179fc-631a-4357-ab64-4d0c598634aa · outbound

This paper cites Rlsf: Reinforce- ment learning via symbolic feedback.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration Rlsf: Reinforce- ment learning via symbolic feedback

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.948733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.948733Z digest=sha256:372664a734a2cd3e9aabed4099b35e4cf9818df0ac9c3b03759a85da77d1e6b1

Observation b6406cbd-e3ed-489f-8a1a-7b072c492817 · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration KTO: Model Alignment as Prospect Theoretic Optimization

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-09T12:11:21.934746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:11:21.934746Z digest=sha256:4f9c43baf82ca0dd6dbb23139df4cd26e7e6e9bb47d31f6470fbfce8a60450ec

Pith citing papers

Observation 3a68a567-d227-4171-b908-2e46e54ca52f · inbound

Aligning Constraint Generation with Design Intent in Parametric CAD cites this paper.

Aligning Constraint Generation with Design Intent in Parametric CAD e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-16T12:18:12.166532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:18:12.166532Z digest=sha256:887a94dcec02fd577ba012c6ca1fef630eb03b81523cab3eb3caab799a8ce9ac

Observation cea00b5b-5162-495a-8cd5-2b1620e498ca · inbound

MechaFormer: Sequence Learning for Kinematic Mechanism Design Automation cites this paper.

MechaFormer: Sequence Learning for Kinematic Mechanism Design Automation e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-08-15T17:35:48.450193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-15T17:35:48.307601Z digest=sha256:c03d7dc310bd12114de4d78cde7ac6e0ed2570f004e9a3fad27dbe7c87e77a86