Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment | Paper Citation Record

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This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

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Observation 7ca5174f-0ea4-406a-a676-b463e0ca9104 · outbound

This paper cites Training language models to follow instructions with human feedback.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Training language models to follow instructions with human feedback

Reference 2

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Observation fa577b07-d0a0-418e-97dd-183650ecf221 · outbound

This paper cites A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future

Reference 3

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Observation 00e2721e-cb01-40d5-ae25-630bdfb76a8c · outbound

This paper cites A Unified Pairwise Framework for RLHF: Bridging Generative Reward Modeling and Policy Optimization.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment A Unified Pairwise Framework for RLHF: Bridging Generative Reward Modeling and Policy Optimization

Reference 4

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Observation 92402796-48dc-41fc-9aea-a29af5247491 · outbound

This paper cites Better Process Supervision with Bi-directional Rewarding Signals.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Better Process Supervision with Bi-directional Rewarding Signals

Reference 5

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Observation 4d239447-3e69-4824-bafa-4fad15c5596c · outbound

This paper cites Reward Function Design in Reinforcement Learning, pages 25–33.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Reward Function Design in Reinforcement Learning, pages 25–33

Reference 6

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Observation be8753fc-b9cb-4731-9515-b7a1cb6c1dab · outbound

This paper cites The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models

Reference 7

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Observation 3289ef25-83b8-40ca-baa2-b91abff2fa82 · outbound

This paper cites Gpt-4 technical report, 2024.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Gpt-4 technical report, 2024

Reference 8

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Observation 21ad8af1-130a-4f9f-bb6f-4d01402cdb91 · outbound

This paper cites Secrets of RLHF in Large Language Models Part II: Reward Modeling.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 9

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Observation 1c8d58a6-9201-4524-b469-2666a30a531d · outbound

This paper cites Skywork-reward: Bag of tricks for reward modeling in llms, October 2024.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Skywork-reward: Bag of tricks for reward modeling in llms, October 2024

Reference 10

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Observation ba77e19c-df9a-46d0-81a4-eeb13a0ea201 · outbound

This paper cites RMB: Comprehensively benchmarking reward models in LLM alignment.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment RMB: Comprehensively benchmarking reward models in LLM alignment

Reference 11

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Observation 082da1a0-2646-43a7-a0a0-e67ca2f656d6 · outbound

This paper cites Helpsteer 2: Open-source dataset for training top-performing reward models.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Helpsteer 2: Open-source dataset for training top-performing reward models

Reference 12

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Observation 60ff893e-87d5-4441-bd2e-aab7d1ffb549 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 13

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Observation 38fba78c-52a5-4611-8f9d-0db0dae359b5 · outbound

This paper cites Impact of preference noise on the alignment performance of generative language models.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Impact of preference noise on the alignment performance of generative language models

Reference 14

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Observation 53221f72-75e5-41ce-849e-7ecbc4f10ae5 · outbound

This paper cites Improving reinforcement learning from human feedback using contrastive rewards, March 2024.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Improving reinforcement learning from human feedback using contrastive rewards, March 2024

Reference 15

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Observation 988419a2-f71a-4481-8f66-eeacda53a897 · outbound

This paper cites Goal misgeneralization in deep reinforcement learning.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Goal misgeneralization in deep reinforcement learning

Reference 16

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Observation fde9f6c0-a8b0-4a72-8da0-9a1a444cf8ee · outbound

This paper cites Scaling laws for reward model overoptimization.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Scaling laws for reward model overoptimization

Reference 17

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Observation f48b4cb1-5d4a-40ed-9ea3-02446c1a41dc · outbound

This paper cites Improving discriminative capability of reward models in rlhf using contrastive learning.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Improving discriminative capability of reward models in rlhf using contrastive learning

Reference 18

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Observation d58fa8a7-78b0-417d-8794-d3fe9ad0c387 · outbound

This paper cites Reward Generalization in RLHF: A Topological Perspective.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Reward Generalization in RLHF: A Topological Perspective

Reference 19

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Observation 2a2abe0b-2f93-4fdb-9f83-54a3fb57ff3b · outbound

This paper cites A note on dpo with noisy preferences & relationship to ipo, 2023.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment A note on dpo with noisy preferences & relationship to ipo, 2023

Reference 20

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Observation 16d62cf5-fd55-4a94-83e5-bc4e82b705ba · outbound

This paper cites Provably robust dpo: aligning language models with noisy feedback.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Provably robust dpo: aligning language models with noisy feedback

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:42.156044Z

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Observation 18218c88-4406-4f6b-8e3e-56db5d47e382 · outbound

This paper cites Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization

Reference 22

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Observation 4157e457-ac76-4f1e-8d66-a8849691436d · outbound

This paper cites ROPO: Robust Preference Optimization for Large Language Models.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment ROPO: Robust Preference Optimization for Large Language Models

Reference 23

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Observation 96fc20ea-3b02-4aca-b22f-12ad442ef022 · outbound

This paper cites Rank analysis of incomplete block designs: I.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Rank analysis of incomplete block designs: I

Reference 24

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This paper cites Inform: Mitigating reward hacking in rlhf via information-theoretic reward modeling.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Inform: Mitigating reward hacking in rlhf via information-theoretic reward modeling

Reference 25

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Observation b8ccced3-09c5-4b76-b69f-9e5cb79926c2 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Direct preference optimization: Your language model is secretly a reward model

Reference 26

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Observation 8ef22d1c-5541-41d8-a330-f0e54ccc63c1 · outbound

This paper cites Confirma- tion bias in human reinforcement learning: Evidence from counterfactual feedback processing.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Confirma- tion bias in human reinforcement learning: Evidence from counterfactual feedback processing

Reference 27

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Observation ba666142-e16b-42e1-9f92-c3b045e2efdb · outbound

This paper cites Pseudo- labeling and confirmation bias in deep semi-supervised learning.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Pseudo- labeling and confirmation bias in deep semi-supervised learning

Reference 28

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Observation cabc74fc-328b-4ccb-9ac2-c5c7083b72f4 · outbound

This paper cites Zephyr: Direct distillation of lm alignment.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Zephyr: Direct distillation of lm alignment

Reference 29

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Observation cf523574-1ae8-40ac-9f1a-f61880f0780e · outbound

This paper cites Smith, and Hannaneh Hajishirzi.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Smith, and Hannaneh Hajishirzi

Reference 30

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This paper cites Rlhf workflow: From reward modeling to online rlhf, 2024.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Rlhf workflow: From reward modeling to online rlhf, 2024

Reference 31

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This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Reference 32

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Observation d782e6c3-2cd6-47a9-abcb-73ed3b3fe353 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 33

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Observation 54fb0898-f685-49e7-ab98-c4c3a1911a67 · outbound

This paper cites Secrets of RLHF in Large Language Models Part I: PPO.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Secrets of RLHF in Large Language Models Part I: PPO

Reference 34

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Observation b550525c-d12b-4d96-b34b-92ca68151aa5 · outbound

This paper cites RM-bench: Benchmarking reward models of language models with subtlety and style.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment RM-bench: Benchmarking reward models of language models with subtlety and style

Reference 35

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Observation 8ff587ba-c6d5-4423-8122-eff6a4e55f94 · outbound

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

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 36

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Observation 5003dbc6-318f-4334-a41e-5cfc9bc965f0 · outbound

This paper cites Weak-to-strong generalization: Eliciting strong capabilities with weak supervision.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Weak-to-strong generalization: Eliciting strong capabilities with weak supervision

Reference 37

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Observation 8a0e4840-f774-4ab0-9b3e-0d7ffa901a37 · outbound

This paper cites Weak-to-strong prefer- ence optimization: Stealing reward from weak aligned model.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Weak-to-strong prefer- ence optimization: Stealing reward from weak aligned model

Reference 38

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Observation eca98603-0169-41fa-8fa7-63551354f620 · outbound

This paper cites Adversarial Training of Reward Models.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Adversarial Training of Reward Models

Reference 39

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This paper cites Defining and charac- terizing reward gaming.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Defining and charac- terizing reward gaming

Reference 40

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Observation b4d11414-6125-41d7-a0b6-b2b415bb0752 · outbound

This paper cites Reward Shaping to Mitigate Reward Hacking in RLHF.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Reward Shaping to Mitigate Reward Hacking in RLHF

Reference 41

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Observation bff2a27b-8fc5-41b3-b048-998c8d611d2c · outbound

This paper cites Odin: disentangled reward mitigates hacking in rlhf.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Odin: disentangled reward mitigates hacking in rlhf

Reference 42

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Observation a467c576-3136-40ee-849e-12726229087b · outbound

This paper cites Taming Overconfidence in LLMs: Reward Calibration in RLHF.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Taming Overconfidence in LLMs: Reward Calibration in RLHF

Reference 43

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Observation 6c73bc40-df62-4342-a705-47d6cbc6fc6c · outbound

This paper cites Overcom- ing reward overoptimization via adversarial policy optimization with lightweight uncertainty estimation, July 2024.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Overcom- ing reward overoptimization via adversarial policy optimization with lightweight uncertainty estimation, July 2024

Reference 44

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Observation eb3802f2-ce7b-42ab-a53c-98f3a8f4f09c · outbound

This paper cites The energy loss phenomenon in rlhf: A new perspective on mitigating reward hacking, February 2025.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment The energy loss phenomenon in rlhf: A new perspective on mitigating reward hacking, February 2025

Reference 45

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Observation 1c655f76-79e9-47ad-b6d7-7eb3abed0f85 · outbound

This paper cites Reward model ensembles help mitigate overoptimizatio.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Reward model ensembles help mitigate overoptimizatio

Reference 46

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Observation 52e9f12e-fc13-45a0-885e-f9273de244d7 · outbound

This paper cites Helping or herding? reward model ensembles mitigate but do not eliminate reward hacking.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Helping or herding? reward model ensembles mitigate but do not eliminate reward hacking

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:42.026701Z

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Observation 100c5a23-f993-43dc-8f28-a38a16053b51 · outbound

This paper cites Reward-robust rlhf in llms, October 2024.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Reward-robust rlhf in llms, October 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:42.019019Z

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Observation 6b50f217-957a-487a-96e1-3f8ebff88faf · outbound

This paper cites Uncertainty-penalized reinforcement learning from human feedback with diverse reward lora ensembles, December 2023.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Uncertainty-penalized reinforcement learning from human feedback with diverse reward lora ensembles, December 2023

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:42.011300Z

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Observation 6b62b461-8298-4123-b4e8-66c177a4693e · outbound

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

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Interpretable prefer- ences via multi-objective reward modeling and mixture-of-experts

Reference 50

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Observation 57244e02-3310-442d-959f-f0d6e96fe115 · outbound

This paper cites RRM: Robust Reward Model Training Mitigates Reward Hacking.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment RRM: Robust Reward Model Training Mitigates Reward Hacking

Reference 51

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Observation f8052a73-4469-45a1-af82-b118f48354af · outbound

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

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment A general theoretical paradigm to understand learning from human preferences

Reference 52

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Observation 94c0d798-619d-468d-a22b-5d7c26826fb4 · outbound

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

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment KTO: Model Alignment as Prospect Theoretic Optimization

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T21:19:41.434016Z

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Observation 951e9b08-4d2f-40db-9183-2f049dbd036b · outbound

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

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Orpo: Monolithic preference optimization without reference model

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.993237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5be45d8c-f341-4446-a2aa-549e0898254b · outbound

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

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Simpo: Simple preference optimization with a reference-free reward

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T21:19:41.440975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0020e4f9-2fa6-4555-a8a1-c7af9ab23f5b · outbound

This paper cites Is dpo superior to ppo for llm alignment? a comprehensive study.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Is dpo superior to ppo for llm alignment? a comprehensive study

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.978016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3b7cb61e-1722-40ea-97b9-284057dc51b6 · outbound

This paper cites Smith, Yejin Choi, and Hannaneh Hajishirzi.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Smith, Yejin Choi, and Hannaneh Hajishirzi

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.968885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c9c7c98f-214b-4e3c-9397-7cc677826137 · outbound

This paper cites Direct Language Model Alignment from Online AI Feedback.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Direct Language Model Alignment from Online AI Feedback

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T21:19:41.451174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d220a40-9759-4e58-a761-1d70cbc63392 · outbound

This paper cites DPO-Shift: Shifting the Distribution of Direct Preference Optimization.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment DPO-Shift: Shifting the Distribution of Direct Preference Optimization

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T21:19:41.454892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9557c46c-3769-4070-9a87-bd0f00de5dd9 · outbound

This paper cites Understanding generalization of preference optimization under noisy feedback.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Understanding generalization of preference optimization under noisy feedback

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.959084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 90ca6071-d427-4f0c-a23d-4cdaa5e807cb · outbound

This paper cites Robust reinforcement learning from corrupted human feedback.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Robust reinforcement learning from corrupted human feedback

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.949483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 19fd781e-d323-47f1-9ff3-051373fba9cc · outbound

This paper cites Theory of games and economic behavior, 60th- anniversary, 2007.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Theory of games and economic behavior, 60th- anniversary, 2007

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.941040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 24cdd193-71e1-4a6d-aec3-67c2dbc7e614 · outbound

This paper cites Multiagent systems: Algorithmic, game-theoretic, and logical foundations.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Multiagent systems: Algorithmic, game-theoretic, and logical foundations

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T21:19:41.468046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f30cc94a-75ce-452a-a767-917d0e9a53e8 · outbound

This paper cites [Yes] " is generally preferable to.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment [Yes] " is generally preferable to

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.926924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 587f0f17-064a-44f2-adff-90fc31e59d3d · outbound

This paper cites Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.918496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2587aa68-18fb-45d6-b3f9-7186901ca14d · outbound

This paper cites Limitations.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Limitations

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.910990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ae68a1d-93c7-4ca9-bf0f-efb0910d40e3 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include theoretical results.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not include theoretical results

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.902892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 45575863-75fc-491c-b97b-d3828cd3544c · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not include experiments

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.894349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 28b3ac97-92c3-44fd-808d-72b200a62c21 · outbound

This paper cites Guidelines: • The answer NA means that paper does not include experiments requiring code.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that paper does not include experiments requiring code

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.884914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ca42c146-6f32-41b1-a962-51a0703b86ee · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not include experiments

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.876158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e4a06e4-3921-4646-909d-6cfebcadef07 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not include experiments

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.866146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e0aa576d-be3d-41bc-a356-eb2cdc6abde9 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not include experiments

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.855662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c43dba8f-bd3f-4f05-ad03-59ed9980f531 · outbound

This paper cites Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.843927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 76be5127-3bb9-4fb1-bdfe-168239b3e32c · outbound

This paper cites an unresolved cited work.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:19:41.828840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 187b16d1-8534-48d7-ba67-1575806c6f2b · outbound

This paper cites an unresolved cited work.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:19:41.811120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a29dce32-996e-4b09-9b85-e560dff6dfb2 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not use existing assets.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not use existing assets

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.792568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 27395a9e-b895-4c14-88eb-bfb3742071e2 · outbound

This paper cites • Researchers should communicate the details of the dataset/code/model as part of their submissions via structured templates.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment • Researchers should communicate the details of the dataset/code/model as part of their submissions via structured templates

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.772923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ec17451-33bb-4202-ad24-41121e2d824b · outbound

This paper cites 32 Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment 32 Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.754738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 009638ff-9737-402e-ab8d-ae28df7ecc55 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.737498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 767017fa-c7a9-451f-8aa4-13ab29e25803 · outbound

This paper cites Answer: [NA] Justification: LLM is used only for editing, or formatting and does not impact the core methodology, scientific rigorousness.

Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment Answer: [NA] Justification: LLM is used only for editing, or formatting and does not impact the core methodology, scientific rigorousness

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:19:41.722866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers