Beyond Factual Correctness: Mitigating Preference-Inconsistent Explanations in Explainable Recommendation | ScienceToStartup | ScienceToStartup

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References (23)

[1]

Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations

2025Cedric Waterschoot, N. Tintarev et al.

[2]

Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation

2025Jinpeng Chen, Jianxiang He et al.

[3]

Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generation

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"PURE enhances explainable recommenders by aligning explanations with user preferences to reduce preference-inconsistent explanations."

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Beyond Factual Correctness: Mitigating Preference-Inconsistent Explanations in Explainable Recommendation

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References (23)

Founder's Pitch

"PURE enhances explainable recommenders by aligning explanations with user preferences to reduce preference-inconsistent explanations."

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Beyond Factual Correctness: Mitigating Preference-Inconsistent Explanations in Explainable Recommendation

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References (23)

Founder's Pitch

"PURE enhances explainable recommenders by aligning explanations with user preferences to reduce preference-inconsistent explanations."

Commercial Viability Breakdown

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