Paper Citation Record · LEDGER

Weighted-Reward Preference Optimization for Implicit Model Fusion

As of 18 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 2 inbound Pith citation observations for arXiv:2412.03187.

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

pith.paper-citation-record.v1
2412.03187 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:48:23.624843Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:51:52.719416Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:11:10.907552Z

Reference resolution

64 of 64 outbound references displayed

verified exact0
verified fuzzy34
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fa2df7e7-2a38-4ae8-81f6-a448f0adc125 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Weighted-Reward Preference Optimization for Implicit Model Fusion Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Source-reported events for the cited work

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Observation c76c5867-7d6f-4880-b9a9-a7566584a428 · outbound

This paper cites A general theoretical paradigm to understand learning from human preferences.

Weighted-Reward Preference Optimization for Implicit Model Fusion A general theoretical paradigm to understand learning from human preferences

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:33.334877Z

Source-reported events for the cited work

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Observation bdb6a074-362c-4ba7-9477-72c4a49ccc0b · outbound

This paper cites Open LLM leaderboard, 2023.

Weighted-Reward Preference Optimization for Implicit Model Fusion Open LLM leaderboard, 2023

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:33.174881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e9b26107-200c-4ea6-8594-0de858eda617 · outbound

This paper cites an unresolved cited work.

Weighted-Reward Preference Optimization for Implicit Model Fusion Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-11T22:48:32.949019Z

Source-reported events for the cited work

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Observation 987c2692-9544-4c07-b914-d8402c1e2058 · outbound

This paper cites InternLM2 Technical Report.

Weighted-Reward Preference Optimization for Implicit Model Fusion InternLM2 Technical Report

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 677a8ea8-e4b1-471b-9057-b5df9428d530 · outbound

This paper cites Chatbot arena: An open platform for evaluating llms by human preference.

Weighted-Reward Preference Optimization for Implicit Model Fusion Chatbot arena: An open platform for evaluating llms by human preference

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:32.842939Z

Source-reported events for the cited work

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Observation 75da1c39-57b2-44ae-9b86-3e9eeef209c1 · outbound

This paper cites Deep reinforcement learning from human preferences.

Weighted-Reward Preference Optimization for Implicit Model Fusion Deep reinforcement learning from human preferences

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:32.691427Z

Source-reported events for the cited work

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Observation 8efe2630-5fd6-480c-a619-03799a56b386 · outbound

This paper cites Bam! born-again multi-task networks for natural language understanding.

Weighted-Reward Preference Optimization for Implicit Model Fusion Bam! born-again multi-task networks for natural language understanding

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:32.555244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4263d49a-429a-4b04-bd54-bb3e996081d2 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Weighted-Reward Preference Optimization for Implicit Model Fusion Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dec28621-fc3c-495a-9e78-847e6f835a64 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Weighted-Reward Preference Optimization for Implicit Model Fusion Training Verifiers to Solve Math Word Problems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:21.244866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99746a63-d289-449a-850a-58eafb68ee0e · outbound

This paper cites UltraFeedback : Boosting language models with high-quality feedback.

Weighted-Reward Preference Optimization for Implicit Model Fusion UltraFeedback : Boosting language models with high-quality feedback

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:32.434853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4775cba0-af72-4f46-8be1-4022df2dfb1e · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Weighted-Reward Preference Optimization for Implicit Model Fusion DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4205d85a-e57f-482f-a4ee-369bee78b7b4 · outbound

This paper cites The Llama 3 Herd of Models.

Weighted-Reward Preference Optimization for Implicit Model Fusion The Llama 3 Herd of Models

Reference 13

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Source-reported events for the cited work

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Observation 20a5d6cd-c4ec-4816-86ff-08c7e97c2fbb · outbound

This paper cites Length-controlled alpacaeval: A simple debiasing of automatic evaluators.

Weighted-Reward Preference Optimization for Implicit Model Fusion Length-controlled alpacaeval: A simple debiasing of automatic evaluators

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:32.266933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8da83c02-4804-4967-9bb1-7eb79634432d · outbound

This paper cites KTO : Model alignment as prospect theoretic optimization.

Weighted-Reward Preference Optimization for Implicit Model Fusion KTO : Model alignment as prospect theoretic optimization

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:32.035409Z

Source-reported events for the cited work

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Observation 2baf45e3-cc3b-4972-a0f4-44b46327981e · outbound

This paper cites Mixture-of-LoRAs : An efficient multitask tuning method for large language models.

Weighted-Reward Preference Optimization for Implicit Model Fusion Mixture-of-LoRAs : An efficient multitask tuning method for large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:31.862767Z

Source-reported events for the cited work

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Observation b06abde6-cfcb-432d-8c9a-76e6b9a41b08 · outbound

This paper cites Knowledge distillation: A survey.

Weighted-Reward Preference Optimization for Implicit Model Fusion Knowledge distillation: A survey

Reference 17

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Source-reported events for the cited work

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Observation a1f363a1-e440-4dc5-928a-8ccb7c20441c · outbound

This paper cites Measuring massive multitask language understanding.

Weighted-Reward Preference Optimization for Implicit Model Fusion Measuring massive multitask language understanding

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:21.603599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa7b7eef-46de-4541-a4d0-aab10c131917 · outbound

This paper cites ORPO : Monolithic preference optimization without reference model.

Weighted-Reward Preference Optimization for Implicit Model Fusion ORPO : Monolithic preference optimization without reference model

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:31.584902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 54fed2fb-f0d6-479c-9507-7c9b79833f0c · outbound

This paper cites Mistral 7B.

Weighted-Reward Preference Optimization for Implicit Model Fusion Mistral 7B

Reference 20

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Source-reported events for the cited work

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Observation 4bb2d512-e04d-45e5-ba3b-8329bef43f20 · outbound

This paper cites LLM-Blender : Ensembling large language models with pairwise ranking and generative fusion.

Weighted-Reward Preference Optimization for Implicit Model Fusion LLM-Blender : Ensembling large language models with pairwise ranking and generative fusion

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:31.424752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 15c4804b-f6ab-4a43-9567-4db7889c7fe1 · outbound

This paper cites Knowledge-augmented reasoning distillation for small language models in knowledge-intensive tasks.

Weighted-Reward Preference Optimization for Implicit Model Fusion Knowledge-augmented reasoning distillation for small language models in knowledge-intensive tasks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:31.284748Z

Source-reported events for the cited work

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Observation fd62c6fa-1447-42cd-9bfc-d72675134404 · outbound

This paper cites Sparse upcycling: Training mixture-of-experts from dense checkpoints.

Weighted-Reward Preference Optimization for Implicit Model Fusion Sparse upcycling: Training mixture-of-experts from dense checkpoints

Reference 23

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Source-reported events for the cited work

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Observation 77196ec9-fd79-4e11-b815-dd2375a1c2a3 · outbound

This paper cites The Winograd schema challenge.

Weighted-Reward Preference Optimization for Implicit Model Fusion The Winograd schema challenge

Reference 24

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Source-reported events for the cited work

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Observation 6fe8371d-ad98-4b69-a366-edf870852903 · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Weighted-Reward Preference Optimization for Implicit Model Fusion From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 25

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Observation ff6ab5db-0b08-48ac-9aab-9da365e0c9c6 · outbound

This paper cites Hashimoto.

Weighted-Reward Preference Optimization for Implicit Model Fusion Hashimoto

Reference 26

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Source-reported events for the cited work

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Observation bbb2b5b4-11a8-4b72-b300-044db28310ad · outbound

This paper cites TruthfulQA : Measuring how models mimic human falsehoods.

Weighted-Reward Preference Optimization for Implicit Model Fusion TruthfulQA : Measuring how models mimic human falsehoods

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:30.724753Z

Source-reported events for the cited work

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Observation f0d68b7d-1d6c-48be-8a21-650a12966267 · outbound

This paper cites Merging models with fisher-weighted averaging.

Weighted-Reward Preference Optimization for Implicit Model Fusion Merging models with fisher-weighted averaging

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:30.623625Z

Source-reported events for the cited work

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Observation f8078d2c-c058-4bb7-9de5-059fc087da29 · outbound

This paper cites Pack of LLM s: Model fusion at test-time via perplexity optimization.

Weighted-Reward Preference Optimization for Implicit Model Fusion Pack of LLM s: Model fusion at test-time via perplexity optimization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:30.463719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bd9bc18c-2682-4fd9-836a-1b4bf1f82c66 · outbound

This paper cites Sim PO : Simple preference optimization with a reference-free reward.

Weighted-Reward Preference Optimization for Implicit Model Fusion Sim PO : Simple preference optimization with a reference-free reward

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:30.351095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3e6431bc-985d-43d4-955b-60e0b6ec7616 · outbound

This paper cites Disentangling Length from Quality in Direct Preference Optimization.

Weighted-Reward Preference Optimization for Implicit Model Fusion Disentangling Length from Quality in Direct Preference Optimization

Reference 31

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Observation 98b82278-b6b4-4165-94e5-789218940319 · outbound

This paper cites Manning, and Chelsea Finn.

Weighted-Reward Preference Optimization for Implicit Model Fusion Manning, and Chelsea Finn

Reference 32

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Observation 79fa6a87-56a2-4519-a243-40057d8fa9ce · outbound

This paper cites Aligning large and small language models via chain-of-thought reasoning.

Weighted-Reward Preference Optimization for Implicit Model Fusion Aligning large and small language models via chain-of-thought reasoning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:29.914920Z

Source-reported events for the cited work

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Observation 2d02388b-eada-4469-abc7-d2ef482a2652 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Weighted-Reward Preference Optimization for Implicit Model Fusion Gemma 2: Improving Open Language Models at a Practical Size

Reference 34

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Observation 95793e4b-f7db-4d41-b673-26c64e9f09cd · outbound

This paper cites Proximal Policy Optimization Algorithms.

Weighted-Reward Preference Optimization for Implicit Model Fusion Proximal Policy Optimization Algorithms

Reference 35

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Observation e92aa4d9-474d-4f0c-9bc9-6f4ec3430183 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Weighted-Reward Preference Optimization for Implicit Model Fusion DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 36

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Observation 6c75fea1-e282-4743-8301-7dbb6bd5d184 · outbound

This paper cites ProFuser : Progressive fusion of large language models.

Weighted-Reward Preference Optimization for Implicit Model Fusion ProFuser : Progressive fusion of large language models

Reference 37

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Observation 48ce57d4-346e-44b1-a248-00e74e220fa3 · outbound

This paper cites Branch-Train-MiX : Mixing expert LLM s into a mixture-of-experts LLM.

Weighted-Reward Preference Optimization for Implicit Model Fusion Branch-Train-MiX : Mixing expert LLM s into a mixture-of-experts LLM

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:29.725257Z

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Observation 5cb99833-72f3-4def-964f-2e007264acdd · outbound

This paper cites Preference fine-tuning of LLM s should leverage suboptimal, on-policy data.

Weighted-Reward Preference Optimization for Implicit Model Fusion Preference fine-tuning of LLM s should leverage suboptimal, on-policy data

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:29.594758Z

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Observation 53601485-ab76-4eb5-b01a-d99134fecfb9 · outbound

This paper cites Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation.

Weighted-Reward Preference Optimization for Implicit Model Fusion Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation

Reference 40

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Observation cbeb0572-5523-4118-999c-ed60c127d4cc · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

Weighted-Reward Preference Optimization for Implicit Model Fusion Zephyr: Direct Distillation of LM Alignment

Reference 41

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Observation db7ad270-3c0a-4181-bbf1-f9b9a35acae2 · outbound

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Weighted-Reward Preference Optimization for Implicit Model Fusion Knowledge fusion of large language models

Reference 42

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Observation 7a3dab9d-288c-4681-b7b4-7da070f5dcbd · outbound

This paper cites Knowledge Fusion of Chat LLMs: A Preliminary Technical Report.

Weighted-Reward Preference Optimization for Implicit Model Fusion Knowledge Fusion of Chat LLMs: A Preliminary Technical Report

Reference 43

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Observation b8f05aee-af0b-445f-8e51-f5f5f1d691e1 · outbound

This paper cites Interpretable preferences via multi-objective reward modeling and mixture-of-experts.

Weighted-Reward Preference Optimization for Implicit Model Fusion Interpretable preferences via multi-objective reward modeling and mixture-of-experts

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:29.307077Z

Source-reported events for the cited work

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Observation 2a071f56-a858-42a1-a01a-5fb58ae6dcfe · outbound

This paper cites Mixture-of-Agents Enhances Large Language Model Capabilities.

Weighted-Reward Preference Optimization for Implicit Model Fusion Mixture-of-Agents Enhances Large Language Model Capabilities

Reference 45

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Observation b8c57ab6-079c-48fc-8754-5faf0619f4f0 · outbound

This paper cites HelpSteer2: Open-source dataset for training top-performing reward models.

Weighted-Reward Preference Optimization for Implicit Model Fusion HelpSteer2: Open-source dataset for training top-performing reward models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:22.834763Z

Source-reported events for the cited work

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Observation 4c16990f-2056-473d-8554-5e27ca8829b0 · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Weighted-Reward Preference Optimization for Implicit Model Fusion Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:29.104760Z

Source-reported events for the cited work

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Observation 508ae4d5-6415-4a6a-b645-a15ab15aebbd · outbound

This paper cites Contrastive preference optimization: Pushing the boundaries of LLM performance in machine translation.

Weighted-Reward Preference Optimization for Implicit Model Fusion Contrastive preference optimization: Pushing the boundaries of LLM performance in machine translation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:28.964747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 19a098c0-1432-4deb-aeb6-0f4256f4e83e · outbound

This paper cites Is DPO superior to PPO for LLM alignment? A comprehensive study.

Weighted-Reward Preference Optimization for Implicit Model Fusion Is DPO superior to PPO for LLM alignment? A comprehensive study

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:28.804771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 003f0bc0-fab0-4a9b-99c9-63d6f8904f28 · outbound

This paper cites Bridging the gap between different vocabularies for llm ensemble.

Weighted-Reward Preference Optimization for Implicit Model Fusion Bridging the gap between different vocabularies for llm ensemble

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:28.614759Z

Source-reported events for the cited work

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Observation a8f40649-ac73-4eff-bd30-c88c3b870f7f · outbound

This paper cites Ties-merging: Resolving interference when merging models.

Weighted-Reward Preference Optimization for Implicit Model Fusion Ties-merging: Resolving interference when merging models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:28.334756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3a4784d0-ecf0-4726-ac29-9a011c6c8908 · outbound

This paper cites Qwen2 Technical Report.

Weighted-Reward Preference Optimization for Implicit Model Fusion Qwen2 Technical Report

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.061399Z

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Observation 05fdfed6-020a-4d50-a75c-2237f08eba29 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Weighted-Reward Preference Optimization for Implicit Model Fusion Yi: Open Foundation Models by 01.AI

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.104877Z

Source-reported events for the cited work

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Observation a8510248-c7dd-4e51-9425-be56280da948 · outbound

This paper cites RRHF : Rank responses to align language models with human feedback.

Weighted-Reward Preference Optimization for Implicit Model Fusion RRHF : Rank responses to align language models with human feedback

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:28.062758Z

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Observation 7bc69922-b776-439d-84b2-10e5fb0a2e97 · outbound

This paper cites H ella S wag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp.\ 4791--4800, 2019.

Weighted-Reward Preference Optimization for Implicit Model Fusion H ella S wag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp.\ 4791--4800, 2019

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:27.924755Z

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Observation 0f707a22-fc9c-4ed6-90c0-2268f4aafa11 · outbound

This paper cites SLiC-HF: Sequence Likelihood Calibration with Human Feedback.

Weighted-Reward Preference Optimization for Implicit Model Fusion SLiC-HF: Sequence Likelihood Calibration with Human Feedback

Reference 56

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Observation 73386b1e-aaac-4504-9d68-1da14a69894e · outbound

This paper cites Judging LLM -as-a-judge with MT-Bench and Chatbot Arena.

Weighted-Reward Preference Optimization for Implicit Model Fusion Judging LLM -as-a-judge with MT-Bench and Chatbot Arena

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:27.787934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a9eae4d2-50ac-4d9d-aaf1-130ba050a408 · outbound

This paper cites WPO : Enhancing RLHF with weighted preference optimization.

Weighted-Reward Preference Optimization for Implicit Model Fusion WPO : Enhancing RLHF with weighted preference optimization

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:27.584759Z

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Observation f3890c95-d620-4ec9-8fb3-9e6d9cd8036f · outbound

This paper cites Starling-7B : Improving helpfulness and harmlessness with RLAIF.

Weighted-Reward Preference Optimization for Implicit Model Fusion Starling-7B : Improving helpfulness and harmlessness with RLAIF

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:48:27.433540Z

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Observation 8fa8b405-7cdd-406c-857f-c41f0bfcb79f · outbound

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

Weighted-Reward Preference Optimization for Implicit Model Fusion Fine-Tuning Language Models from Human Preferences

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.454765Z

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Observation 9ffb35a9-2081-4577-9e53-59e0adfdc756 · outbound

This paper cites write newline.

Weighted-Reward Preference Optimization for Implicit Model Fusion write newline

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.495146Z

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Observation 16127d6e-d884-4d43-a4b4-7dfe77098d2b · outbound

This paper cites @esa (Ref.

Weighted-Reward Preference Optimization for Implicit Model Fusion @esa (Ref

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.526871Z

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Observation 834b00d9-0ed4-4f10-a813-3308cfe5dc31 · outbound

This paper cites an unresolved cited work.

Weighted-Reward Preference Optimization for Implicit Model Fusion Unresolved cited work

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.574761Z

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Observation 18d18745-b8f2-4f41-94bf-afcf3eaf9f6e · outbound

This paper cites an unresolved cited work.

Weighted-Reward Preference Optimization for Implicit Model Fusion Unresolved cited work

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-11T22:48:23.624843Z

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Pith citing papers

Observation a0e3fefa-5e6f-441f-8143-9a1d15942330 · inbound

An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems cites this paper.

An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems Weighted-Reward Preference Optimization for Implicit Model Fusion

Reference 143

Resolution: unresolved; no resolver link, observed 2026-08-10T22:51:52.719416Z

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Observation 048901a7-3233-4835-a467-f5e9c1f57323 · inbound

CortexDebate: Debating Sparsely and Equally for Multi-Agent Debate cites this paper.

CortexDebate: Debating Sparsely and Equally for Multi-Agent Debate Weighted-Reward Preference Optimization for Implicit Model Fusion

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:11:10.913347Z

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