Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation | Paper Citation Record

Observation 1406ae7f-5281-4b39-ac1c-a021f9161497 · outbound

This paper cites Spatiotemporal-Enhanced Network for Click-Through Rate Prediction in Location-based Services.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Spatiotemporal-Enhanced Network for Click-Through Rate Prediction in Location-based Services

Reference 1

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Observation 832cdc81-7ee4-4e17-b93e-32f7398edca3 · outbound

This paper cites Spatial-temporal knowledge distillation for takeaway recommendation.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Spatial-temporal knowledge distillation for takeaway recommendation

Reference 2

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Observation eaf2372c-da42-4bb3-92a6-b11d4f0451ba · outbound

This paper cites Rest: A plug-and-play spatially- constrained representation enhancement framework for local-life recommenda- tion.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Rest: A plug-and-play spatially- constrained representation enhancement framework for local-life recommenda- tion

Reference 3

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Observation bb9e1c0c-7a3f-4469-907c-ee5bc101d8a2 · outbound

This paper cites Localgpt: Bench- marking and advancing large language models for local life services in meituan.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Localgpt: Bench- marking and advancing large language models for local life services in meituan

Reference 4

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Observation 0f2eb3f5-afc4-4d6c-afbe-cab75a4944f1 · outbound

This paper cites Fragment and integrate network (fin): A novel spatial- temporal modeling based on long sequential behavior for online food ordering click-through rate prediction.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Fragment and integrate network (fin): A novel spatial- temporal modeling based on long sequential behavior for online food ordering click-through rate prediction

Reference 5

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Observation 3909b714-c515-41e3-859c-b489f79d33a6 · outbound

This paper cites Fim: Frequency-aware multi-view interest modeling for local-life service recommendation.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Fim: Frequency-aware multi-view interest modeling for local-life service recommendation

Reference 6

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Observation 28e11412-206a-405e-82e2-55800e7da6dd · outbound

This paper cites Llm-aligned geographic item tokenization for local-life recommendation.arXiv preprint arXiv:2511.14221, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Llm-aligned geographic item tokenization for local-life recommendation.arXiv preprint arXiv:2511.14221, 2025

Reference 7

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Observation be2b2ed0-9c91-4ef1-bae6-6199a1a6bf9f · outbound

This paper cites OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service

Reference 8

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Observation 0c3991a7-aa55-4ff0-aca1-b16083d49e51 · outbound

This paper cites Reasoning Over Space: Enabling Geographic Reasoning for LLM-Based Generative Next POI Recommendation.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Reasoning Over Space: Enabling Geographic Reasoning for LLM-Based Generative Next POI Recommendation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:46.643416Z

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Observation feceef6a-12e9-489f-a43f-5c576078e873 · outbound

This paper cites Deep interest evolution network for click-through rate prediction.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Deep interest evolution network for click-through rate prediction

Reference 10

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Observation 2e7e6594-9088-40ad-95d9-c0d8c7f01bbe · outbound

This paper cites Dynamic forgetting and spatio- temporal periodic interest modeling for local-life service recommendation.arXiv preprint arXiv:2508.02451, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Dynamic forgetting and spatio- temporal periodic interest modeling for local-life service recommendation.arXiv preprint arXiv:2508.02451, 2025

Reference 11

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Observation 55746831-5ea9-4090-8fd2-e76c0ee6a1a4 · outbound

This paper cites Next-poi recommendation via spatial-temporal knowledge graph contrastive learning and trajectory prompt.IEEE Transactions on Knowl- edge and Data Engineering, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Next-poi recommendation via spatial-temporal knowledge graph contrastive learning and trajectory prompt.IEEE Transactions on Knowl- edge and Data Engineering, 2025

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:46.884631Z

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Observation 8b060e28-d394-4025-adf8-946d5cf60ca7 · outbound

This paper cites Next point-of-interest (poi) recommendation model based on multi-modal spatio-temporal context feature embedding.arXiv preprint arXiv:2509.22661, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Next point-of-interest (poi) recommendation model based on multi-modal spatio-temporal context feature embedding.arXiv preprint arXiv:2509.22661, 2025

Reference 13

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Observation c8c510da-b6d0-400f-947c-38d94ae0059e · outbound

This paper cites Integrating personalized spatio-temporal clustering for next poi recommendation.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Integrating personalized spatio-temporal clustering for next poi recommendation

Reference 14

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Observation 777c6fbc-c088-4595-9d12-da8ad63469c1 · outbound

This paper cites Video corpus moment retrieval with query-specific context learning and progressive localization.IEEE Transactions on Circuits and Systems for Video Technology, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Video corpus moment retrieval with query-specific context learning and progressive localization.IEEE Transactions on Circuits and Systems for Video Technology, 2025

Reference 15

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Observation 135a1133-c6e6-440a-bb43-c6b299ef1251 · outbound

This paper cites Qwen3 Technical Report.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Qwen3 Technical Report

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Observation e4ae0256-91fd-4019-9e4b-e11cfc7676ab · outbound

This paper cites DeepSeek-V3 Technical Report.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation DeepSeek-V3 Technical Report

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Observation 337f3505-900c-437f-8fe6-5fc5d18ed4f6 · outbound

This paper cites Recommender systems with generative retrieval.Advances in Neural Information Processing Systems, 36:10299–10315, 2023.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Recommender systems with generative retrieval.Advances in Neural Information Processing Systems, 36:10299–10315, 2023

Reference 18

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Observation 4600a288-0602-4268-899b-0d547bf0011d · outbound

This paper cites Adapting large language models by integrating collaborative semantics for recommendation.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Adapting large language models by integrating collaborative semantics for recommendation

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Observation 99300001-762f-4d6c-9022-41f52a84c8c5 · outbound

This paper cites Qarm: Quantitative alignment multi-modal recommendation at kuaishou.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Qarm: Quantitative alignment multi-modal recommendation at kuaishou

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Observation e4b2425c-effe-46cc-9bc1-8eb069c4c55d · outbound

This paper cites Generative next poi recommendation with semantic id.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Generative next poi recommendation with semantic id

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Observation 599e7670-c735-4cb7-b4a1-c48282a864aa · outbound

This paper cites FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets

Reference 22

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Observation 211a2ab1-67d2-424a-b9b0-24b44b08baab · outbound

This paper cites Mmq: Multimodal mixture-of- quantization tokenization for semantic id generation and user behavioral adap- tation.arXiv preprint arXiv:2508.15281, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Mmq: Multimodal mixture-of- quantization tokenization for semantic id generation and user behavioral adap- tation.arXiv preprint arXiv:2508.15281, 2025

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Observation 04f84212-ea78-47e4-9842-c108a23d949c · outbound

This paper cites Enhancing Partially Relevant Video Retrieval with Robust Alignment Learning.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Enhancing Partially Relevant Video Retrieval with Robust Alignment Learning

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Observation d0ed7345-61c5-4552-9a25-3597e3eaa0fc · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Representation Engineering: A Top-Down Approach to AI Transparency

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Observation d60c9534-a6f9-4b59-9a4b-40ca23dae891 · outbound

This paper cites Enhancing multiple dimensions of trustworthiness in llms via sparse activation control.Advances in Neural Information Processing Systems, 37:15730–15764, 2024.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Enhancing multiple dimensions of trustworthiness in llms via sparse activation control.Advances in Neural Information Processing Systems, 37:15730–15764, 2024

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Observation e54c15dd-d7b2-429e-a4c0-ef1f9f156fea · outbound

This paper cites Steering knowledge selection behaviours in llms via sae-based representation engineering.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Steering knowledge selection behaviours in llms via sae-based representation engineering

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Observation 6cfd6782-79af-4241-ac82-4ddc47c31f29 · outbound

This paper cites Episodic memory repre- sentation for long-form video understanding.arXiv preprint arXiv:2508.09486, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Episodic memory repre- sentation for long-form video understanding.arXiv preprint arXiv:2508.09486, 2025

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Observation caa8e970-e7c0-4417-a4d7-a36130b4e72f · outbound

This paper cites Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering

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Observation d6c6c1cd-21ca-4061-94f1-622d9c1d0c0e · outbound

This paper cites An Embedding Learning Framework for Numerical Features in CTR Prediction.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation An Embedding Learning Framework for Numerical Features in CTR Prediction

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Observation 8a298b15-ae8b-472d-8706-db05d55a4f4b · outbound

This paper cites Deep & cross network for ad click predictions.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Deep & cross network for ad click predictions

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This paper cites Deep interest network for click-through rate prediction.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Deep interest network for click-through rate prediction

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Observation 844f9b52-4f39-487d-b834-9e1e5d1ff9a1 · outbound

This paper cites Learnable item tokenization for generative recommendation.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Learnable item tokenization for generative recommendation

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Observation e0fa24c2-e309-46d4-8401-f27a551591ed · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Eager: Two-stream generative recommender with behavior-semantic collaboration

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Observation 96466dc8-3678-419a-bd10-db9c21f49b0a · outbound

This paper cites Onerec technical report.arXiv preprint arXiv:2506.13695, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Onerec technical report.arXiv preprint arXiv:2506.13695, 2025

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation OneRec-V2 Technical Report

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Recbase: Generative foundation model pretraining for zero-shot recommendation

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Observation 9da94bcf-622a-4c97-b612-ee65f4c0523a · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations

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Observation 36b426bb-3f5d-47f5-862a-d57767b2e286 · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks

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Observation 3d517114-67bb-424d-9d66-1bc20771db72 · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Unified Semantic and ID Representation Learning for Deep Recommenders

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Observation e72ac69e-5608-4a0e-929e-3a4f5e2d337c · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID

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Observation 21b133eb-b5f7-48b9-ad03-79c144f9e806 · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Language models as semantic indexers

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Observation 897b25fb-197d-4c31-b948-48d9d1d41a38 · outbound

This paper cites Plum: Adapting pre-trained language models for industrial-scale generative recommendations.arXiv preprint arXiv:2510.07784, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Plum: Adapting pre-trained language models for industrial-scale generative recommendations.arXiv preprint arXiv:2510.07784, 2025

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Personalized prompt learning for explain- able recommendation.ACM Transactions on Information Systems, 41(4):1–26, 2023

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Observation c6269cd4-5a00-4483-94ff-7f2fca22b874 · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Onerec-think: In-text reasoning for generative recommendation.arXiv preprint arXiv:2510.11639, 2025

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Probing classifiers: Promises, shortcomings, and advances

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Inference-time intervention: Eliciting truthful answers from a language model.Advances in Neural Information Processing Systems, 36:41451–41530, 2023

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation The linear representation hy- pothesis and the geometry of large language models

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Observation e4c29ce2-6801-46f4-af5b-0d89ae0c1a81 · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Patchscopes: a unifying framework for inspecting hidden representations of language models

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Observation b7e6e0af-fad9-4091-a9b7-e226fa1cc131 · outbound

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Activation scaling for steering and interpreting language models

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Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Training Large Language Models to Reason in a Continuous Latent Space

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Observation 926dc58b-879c-4722-aeff-9eb8be9257a5 · outbound

This paper cites Blip-2: bootstrapping language-image pre-training with frozen image encoders and large language models.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Blip-2: bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.011412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23f4ee79-e922-4a4d-be13-595bd63539c4 · outbound

This paper cites Object-centric learning with slot attention.Advances in neural information processing systems, 33:11525–11538, 2020.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Object-centric learning with slot attention.Advances in neural information processing systems, 33:11525–11538, 2020

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.015477Z

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Observation e70d3844-307d-4e47-904b-a166d5c896e2 · outbound

This paper cites End-to-end object detection with transformers.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation End-to-end object detection with transformers

Reference 55

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.019497Z

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Observation d78bd215-ab3d-4ccf-bc0b-08c3581dbe35 · outbound

This paper cites Attention is not all you need: Pure attention loses rank doubly exponentially with depth.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Attention is not all you need: Pure attention loses rank doubly exponentially with depth

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.023472Z

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Observation be4e455d-6050-46bf-a77c-5a351f99c79d · outbound

This paper cites The power of scale for parameter- efficient prompt tuning.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation The power of scale for parameter- efficient prompt tuning

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.027643Z

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Observation 1bfb7fdf-7561-4f8f-94b1-d55ded6e1efb · outbound

This paper cites Rezero is all you need: Fast convergence at large depth.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Rezero is all you need: Fast convergence at large depth

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.031667Z

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Observation 7b095d63-047e-48b8-a434-01d793978070 · outbound

This paper cites Highway Networks.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Highway Networks

Reference 59

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.035867Z

Source-reported events for the cited work

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Observation 71028136-a383-4e37-a7b7-58d7fd6fb468 · outbound

This paper cites End-to-End User Behavior Retrieval in Click-Through RatePrediction Model.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation End-to-End User Behavior Retrieval in Click-Through RatePrediction Model

Reference 60

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.040235Z

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Observation 091fbaf8-4c95-4518-9a32-c4b7908b3ff9 · outbound

This paper cites Search-based user interest modeling with lifelong sequential behavior data for click-through rate prediction.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Search-based user interest modeling with lifelong sequential behavior data for click-through rate prediction

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.044406Z

Source-reported events for the cited work

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Observation 773e3131-63bb-479b-b569-c44185a1c793 · outbound

This paper cites Twin v2: Scal- ing ultra-long user behavior sequence modeling for enhanced ctr prediction at kuaishou.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Twin v2: Scal- ing ultra-long user behavior sequence modeling for enhanced ctr prediction at kuaishou

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.048434Z

Source-reported events for the cited work

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Observation 68bcb66b-a475-4bc4-a654-963d18caf426 · outbound

This paper cites Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.052385Z

Source-reported events for the cited work

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Observation 74b8d064-6304-4972-a71a-53e4e029c26a · outbound

This paper cites Rankmixer: Scaling up ranking models in industrial recommenders.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Rankmixer: Scaling up ranking models in industrial recommenders

Reference 64

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.056654Z

Source-reported events for the cited work

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Observation 99c3a536-4df4-4a73-a510-b5e495b6007d · outbound

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

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Session-based Recommendations with Recurrent Neural Networks

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.060892Z

Source-reported events for the cited work

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Observation 45d28ac6-e0c9-49bf-9a69-2efcb6d86f37 · outbound

This paper cites Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.065027Z

Source-reported events for the cited work

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Observation 4c0824dc-d2a9-42b9-a9a4-85b7f82cdcf9 · outbound

This paper cites Self-attentive sequential recommenda- tion.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Self-attentive sequential recommenda- tion

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.069157Z

Source-reported events for the cited work

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Observation b98465eb-de72-4515-b04d-ffbb85d4ef18 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.073050Z

Source-reported events for the cited work

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Observation be490594-90da-4fb6-80d4-559de082540d · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741, 2023.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Direct preference optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741, 2023

Reference 69

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.077317Z

Source-reported events for the cited work

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Observation fc08e1b0-96e0-4522-a215-0b775ef45d2c · outbound

This paper cites Qwen3 technical report, 2025.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Qwen3 technical report, 2025

Reference 70

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.081227Z

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Observation 895e0ccf-7a33-42c1-9c6d-07198f9d8a38 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-31T22:39:50.086546Z

Source-reported events for the cited work

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Observation 97766b6a-394f-4440-87de-e3f70bea60f4 · outbound

This paper cites Decoupled Weight Decay Regularization.

Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation Decoupled Weight Decay Regularization

Reference 72

Resolution: malformed identifier; no resolver link, observed 2026-07-31T22:39:50.090484Z

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