LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation | Paper Citation Record

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation GPT-4 Technical Report

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This paper cites Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

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This paper cites Evaluating Position Bias in Large Language Model Recommendations.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Evaluating Position Bias in Large Language Model Recommendations

Reference 7

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This paper cites Aligning Large Language Models with Recommendation Knowledge.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Aligning Large Language Models with Recommendation Knowledge

Reference 8

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

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This paper cites On Softmax Direct Preference Optimization for Recommendation.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation On Softmax Direct Preference Optimization for Recommendation

Reference 11

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation InProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation The Llama 3 Herd of Models

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

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This paper cites Session-based Recommendations with Recurrent Neural Networks.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Session-based Recommendations with Recurrent Neural Networks

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This paper cites Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

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This paper cites STAR: A Simple Training-free Approach for Recommendations using Large Language Models.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation STAR: A Simple Training-free Approach for Recommendations using Large Language Models

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This paper cites Large Language Models for Generative Recommendation: A Survey and Visionary Discussions.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Large Language Models for Generative Recommendation: A Survey and Visionary Discussions

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This paper cites E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation The Implicit Length Bias of Label Smoothing on Beam Search Decoding

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation RosePO: Aligning LLM-based Recommenders with Human Values

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Large Language Models are Not Stable Recommender Systems

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Using Captum to Explain Generative Language Models

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Correcting Length Bias in Neural Machine Translation

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search Degradation

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation InProceedings of the 28th ACM international conference on information and knowledge management

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Large Language Models Enhanced Collaborative Filtering

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Qwen2 Technical Report

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Attention Is All You Need

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Zero-Shot Next-Item Recommendation using Large Pretrained Language Models

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

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LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

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Observation ca0d7e87-456d-40a5-97fd-d97356d0f903 · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efd9ee1f-f054-40d7-92fb-27e96cbd37f6 · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bf0e0dd-989a-4a67-98f8-38675d0545ff · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 68

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59a9aa73-864a-4f42-ae74-4f15bbe21323 · outbound

This paper cites Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f179dd22-e1f5-4f20-a1dd-d85500c4c24f · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 70

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d6e38f9-d419-4729-9c88-2b6618ef5679 · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cab07d0d-252f-48b0-95e6-e68187864492 · outbound

This paper cites Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e81b9d86-3539-4a5a-b3ba-21874fed490d · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41cc5308-5e4b-4d58-bb6f-1222a7bc75fd · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28b54319-0f79-4b1e-b7a3-fb6cee533e45 · outbound

This paper cites an unresolved cited work.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation Unresolved cited work

Reference 75

Resolution: unresolved; no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

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Outbound references

Pith citing papers