Paper Citation Record · LEDGER

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

As of 20 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 8 inbound Pith citation observations for arXiv:2506.05069.

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

pith.paper-citation-record.v1
2506.05069 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:31:40.014612Z

measured 73 of 73 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:38:07.504889Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:05:03.746106Z

Reference resolution

65 of 65 outbound references displayed

verified exact0
verified fuzzy39
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a9d8d624-e92f-4e7b-95e6-0e08dfc54f50 · outbound

This paper cites Tallrec: An effective and efficient tuning framework to align large language model with recommendation.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Tallrec: An effective and efficient tuning framework to align large language model with recommendation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:35.435361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb7325b1-a9be-4450-9c91-eda3ef106e6b · outbound

This paper cites Uncovering chatgpt’s capabilities in recommender systems.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Uncovering chatgpt’s capabilities in recommender systems

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.796879Z

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 9edcb960-1201-417b-867d-c87d1afde31c · outbound

This paper cites Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5), 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5), 2023

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:35.752126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 655d6982-b0e1-4b69-a603-270a93ae86ee · outbound

This paper cites Llara: Large language-recommendation assistant, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Llara: Large language-recommendation assistant, 2024

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.778350Z

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 388b9785-1e07-4e25-9347-cd805518ec98 · outbound

This paper cites Is chatgpt a good recommender? a preliminary study, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Is chatgpt a good recommender? a preliminary study, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.766895Z

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 f11ed3b6-844b-4a90-896c-cd7ad23fd0da · outbound

This paper cites Improving llm-powered recommendations with personalized information, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Improving llm-powered recommendations with personalized information, 2025

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.755359Z

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 9945e07f-24d3-4d00-9315-437d3223df8b · outbound

This paper cites Let me do it for you: Towards llm empowered recommendation via tool learning.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Let me do it for you: Towards llm empowered recommendation via tool learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.743357Z

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 e2a64946-7664-44ea-9dec-8c39df6b7ce3 · outbound

This paper cites Collaborative retrieval for large language model-based conversational recommender systems, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Collaborative retrieval for large language model-based conversational recommender systems, 2025

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.731853Z

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 469d1a14-96ff-4fde-96de-464d916e8a85 · outbound

This paper cites AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:36.626072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3cce80e-585c-401a-8eb6-617434fb61b3 · outbound

This paper cites Agentsociety challenge: Designing llm agents for user modeling and recommendation on web platforms.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Agentsociety challenge: Designing llm agents for user modeling and recommendation on web platforms

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:36.759054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ed5a6d7-ff84-478d-ba84-28bbbfd07976 · outbound

This paper cites Think before recommend: Unleashing the latent reasoning power for sequential recommenda- tion, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Think before recommend: Unleashing the latent reasoning power for sequential recommenda- tion, 2025

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.714341Z

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 32710d2c-70e8-49eb-b7eb-10e78be8090a · outbound

This paper cites Got4rec: Graph of thoughts for sequential recommendation, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Got4rec: Graph of thoughts for sequential recommendation, 2025

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.702040Z

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 9ce3e3dc-69d9-44ac-8015-a1be3191b5a9 · outbound

This paper cites Cot4rec: Revealing user preferences through chain of thought for recommender systems.Proceedings of the AAAI Conference on Artificial Intelligence, 39(12):13142–13151, Apr.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Cot4rec: Revealing user preferences through chain of thought for recommender systems.Proceedings of the AAAI Conference on Artificial Intelligence, 39(12):13142–13151, Apr

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.688462Z

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 35a9b1a6-2a61-4d86-a98f-0054405fc6fa · outbound

This paper cites Chain-of-thought prompting empowered generative user modeling for personalized recommendation.Neural Computing and Applications, 36(34):21723–21742, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Chain-of-thought prompting empowered generative user modeling for personalized recommendation.Neural Computing and Applications, 36(34):21723–21742, 2024

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.674134Z

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 64f9bc28-698b-41b9-897a-858d0977a84d · outbound

This paper cites s1: Simple test-time scaling, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation s1: Simple test-time scaling, 2025

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.661953Z

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 296936c6-d145-4001-a643-6959d7de1810 · outbound

This paper cites Light-r1: Curriculum sft, dpo and rl for long cot from scratch and beyond, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Light-r1: Curriculum sft, dpo and rl for long cot from scratch and beyond, 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:37.606301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40fcbc9d-9a2a-418f-abbe-1eb37da7082d · outbound

This paper cites Can 1b llm surpass 405b llm? rethinking compute-optimal test-time scaling, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Can 1b llm surpass 405b llm? rethinking compute-optimal test-time scaling, 2025

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.641904Z

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 e5eb0671-5673-4cfb-81d5-9f75762b7f5f · outbound

This paper cites Limo: Less is more for reasoning, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Limo: Less is more for reasoning, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:37.852254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dfc5291-9863-4f4e-b904-0db14a0913c8 · outbound

This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:38.306557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be7a9f7d-7381-4004-ae5b-fa0f886e0f97 · outbound

This paper cites Prompt learning for news recommendation.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Prompt learning for news recommendation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.621151Z

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 474df0c9-3c36-4991-be0d-4abed80f5487 · outbound

This paper cites Towards understanding and mitigating unintended biases in language model-driven conversational rec- ommendation.Information Processing & Management, 60(1):103139, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Towards understanding and mitigating unintended biases in language model-driven conversational rec- ommendation.Information Processing & Management, 60(1):103139, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.607326Z

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 1ff022d6-2047-415e-8069-4a5d12121387 · outbound

This paper cites Improving conversational recommenda- tion systems’ quality with context-aware item meta information, 2021.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Improving conversational recommenda- tion systems’ quality with context-aware item meta information, 2021

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.591587Z

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 cc85e229-b1fa-4f17-8794-bf45b4f79ef0 · outbound

This paper cites Recommendation as instruction following: A large language model empowered recommendation approach, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Recommendation as instruction following: A large language model empowered recommendation approach, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.580278Z

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 f73c37bd-50c3-4ff4-838f-da03663cd9ba · outbound

This paper cites Personalized prompt learning for explainable recommen- dation, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Personalized prompt learning for explainable recommen- dation, 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.567561Z

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 27577f6a-da83-4bfe-8e2b-32d67bcf4148 · outbound

This paper cites Bridging items and language: A transition paradigm for large language model-based recommendation, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Bridging items and language: A transition paradigm for large language model-based recommendation, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.554417Z

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 e71cd1ae-f502-4d4c-9e11-cac26fda931e · outbound

This paper cites Dapo: An open-source llm reinforcement learning system at scale, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Dapo: An open-source llm reinforcement learning system at scale, 2025

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.731275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04dcd98b-694b-402c-b000-7dd61ac16ed6 · outbound

This paper cites Vapo: Efficient and reliable reinforcement learning for advanced reasoning tasks, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Vapo: Efficient and reliable reinforcement learning for advanced reasoning tasks, 2025

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.751064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 109f20ad-f26a-47f9-a4dc-d25cad2adda7 · outbound

This paper cites an unresolved cited work.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.825478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0be8530e-8641-4084-9e42-a99f768648eb · outbound

This paper cites Reinforce++: An efficient rlhf algorithm with robustness to both prompt and reward models, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Reinforce++: An efficient rlhf algorithm with robustness to both prompt and reward models, 2025

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.523283Z

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 adbf7bc7-44f4-433d-a51d-15476545ef11 · outbound

This paper cites OpenAI o1 System Card.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation OpenAI o1 System Card

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.861633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7930238a-8fd9-4e71-8920-dfe068494ac8 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.867098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c7a147e-5174-4005-a56a-a3f32807754a · outbound

This paper cites Reft: Reasoning with reinforced fine-tuning, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Reft: Reasoning with reinforced fine-tuning, 2024

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.874155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ee1227d-7a6e-48b0-900c-89c15f19988c · outbound

This paper cites Maxwell Harper and Joseph A.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Maxwell Harper and Joseph A

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.879666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54681240-9bbb-44f9-81ff-4160d43fcbb7 · outbound

This paper cites Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.885852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e5bf24e-4b74-4c6d-a3e2-4d8ee8ad73d9 · outbound

This paper cites Neural graph collabo- rative filtering.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Neural graph collabo- rative filtering

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.497734Z

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 0d5194f6-4f84-4e55-b49c-5acc8ea52e20 · outbound

This paper cites Hop-rec: high- order proximity for implicit recommendation.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Hop-rec: high- order proximity for implicit recommendation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.482737Z

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 f5e6e79a-91b0-464a-87f3-77dfb0c2383f · outbound

This paper cites Hamilton, Rex Ying, and Jure Leskovec.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Hamilton, Rex Ying, and Jure Leskovec

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.907154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a039ec6-c1b2-487b-8fa1-aa1fe692a8e8 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolution network for recommendation, 2020.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Lightgcn: Simplifying and powering graph convolution network for recommendation, 2020

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.463150Z

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 76eef3da-b459-4fb9-bba6-77ac403e2ee2 · outbound

This paper cites Graph-based embedding smoothing for sequential recommendation.IEEE Transactions on Knowledge and Data Engineering, 35(1):496–508, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Graph-based embedding smoothing for sequential recommendation.IEEE Transactions on Knowledge and Data Engineering, 35(1):496–508, 2023

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.449369Z

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 d7ce2e96-c8df-414b-8dfa-46293cf645f7 · outbound

This paper cites Sequential recommendation with graph neural networks, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Sequential recommendation with graph neural networks, 2023

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.437266Z

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 2b3b3e80-eec7-4fe6-bf37-c18cd43496b8 · outbound

This paper cites Dynamic graph neural networks for sequential recommendation, 2021.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Dynamic graph neural networks for sequential recommendation, 2021

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.424475Z

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 a7b60504-3ab7-4f50-85c5-7ddd51341b22 · outbound

This paper cites Knowledge-enhanced graph neural networks for sequential recommendation.Information, 11(8), 2020.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Knowledge-enhanced graph neural networks for sequential recommendation.Information, 11(8), 2020

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.414508Z

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 3fd8112d-607d-41c1-b0cd-bf970f05b2c5 · outbound

This paper cites Invisible walls in cities: Leveraging large language models to predict urban segregation experience with social media content.arXiv preprint arXiv:2503.04773, 2025.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Invisible walls in cities: Leveraging large language models to predict urban segregation experience with social media content.arXiv preprint arXiv:2503.04773, 2025

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.935597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c62e192-1223-4ac0-b190-1e0ed88a7784 · outbound

This paper cites Large language model-driven meta-structure discovery in heterogeneous information network.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Large language model-driven meta-structure discovery in heterogeneous information network

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.939032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cf37803-a597-49b0-ac95-6170f86d54a0 · outbound

This paper cites HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.942384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db17b75a-981d-40a8-a4cb-3fd55a0a4241 · outbound

This paper cites KCTS: Knowledge- constrained tree search decoding with token-level hallucination detection.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation KCTS: Knowledge- constrained tree search decoding with token-level hallucination detection

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.397850Z

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 d0943b0c-bcf4-4442-9215-57cbf9baa68b · outbound

This paper cites Language agent tree search unifies reasoning acting and planning in language models, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Language agent tree search unifies reasoning acting and planning in language models, 2024

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.388079Z

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 38aac20e-9e33-4baa-a39d-421c37fd2da4 · outbound

This paper cites Tenenbaum, and Chuang Gan.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Tenenbaum, and Chuang Gan

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.953539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 928e9074-3420-4316-9e8f-eda54a4eb34d · outbound

This paper cites Don’t throw away your value model! generating more preferable text with value-guided monte-carlo tree search decoding, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Don’t throw away your value model! generating more preferable text with value-guided monte-carlo tree search decoding, 2024

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.371184Z

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 529b7155-4401-44a0-9c3e-a7d47e026a8c · outbound

This paper cites A simple model of inference scaling laws, 2024.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation A simple model of inference scaling laws, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.361448Z

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 ba416c12-ae19-4821-860d-9c3f14a3429e · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Self-consistency improves chain of thought reasoning in language models, 2023

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.964302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27c0e4d7-e80a-4953-b39a-aef87de9d962 · outbound

This paper cites Le, Christopher Ré, and Azalia Mirhoseini.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Le, Christopher Ré, and Azalia Mirhoseini

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.967906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9690b752-126d-4007-baa8-b50d61c2b4b2 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.971571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f72a6b70-248c-445e-ba66-5f5625ef600e · outbound

This paper cites M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.975207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cc8a456-b1bd-40ee-9a4a-5003db581815 · outbound

This paper cites Large language models are zero-shot rankers for recommender systems.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Large language models are zero-shot rankers for recommender systems

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.978763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2b89212-40fb-45a1-a847-f461203625ef · outbound

This paper cites Chat-rec: Towards interactive and explainable llms-augmented recommender system, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Chat-rec: Towards interactive and explainable llms-augmented recommender system, 2023

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.334003Z

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 cc51d02e-eaa0-419a-bfc9-fd5f3a442e9b · outbound

This paper cites Learning vector-quantized item representation for transferable sequential recommenders, 2023.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Learning vector-quantized item representation for transferable sequential recommenders, 2023

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.324083Z

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 6235838c-fbb6-4851-ac38-e96fcb801ba7 · outbound

This paper cites Towards universal sequence representation learning for recommender systems, 2022.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Towards universal sequence representation learning for recommender systems, 2022

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.314173Z

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 bb29f070-1785-4a6f-9e35-f59bf1adbcda · outbound

This paper cites Where to go next for recommender systems? id- vs.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Where to go next for recommender systems? id- vs

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.303991Z

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 137514b3-97ae-415c-9362-88979be7c039 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T10:31:39.996738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38b6f274-8f69-468a-9041-953480100aba · outbound

This paper cites Session-based recommendations with recurrent neural networks, 2016.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Session-based recommendations with recurrent neural networks, 2016

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.286570Z

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 5b90a9ae-b371-4a24-b812-9a5ec8b9e1f6 · outbound

This paper cites Personalized top-n sequential recommendation via convolutional sequence embedding, 2018.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Personalized top-n sequential recommendation via convolutional sequence embedding, 2018

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.273946Z

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 2cb05821-85bd-4b6a-ae82-50c8e9ff9978 · outbound

This paper cites Self-attentive sequential recommendation, 2018.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation Self-attentive sequential recommendation, 2018

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.258443Z

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 081da871-16eb-4a2c-b5e4-28be1063e5d0 · outbound

This paper cites The reasoning process must comply with the following requirements: 1.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation The reasoning process must comply with the following requirements: 1

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.243155Z

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 f7674c48-2c9b-44b6-adca-16a187597052 · outbound

This paper cites The answers provided are only to guide your reasoning process.

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation The answers provided are only to guide your reasoning process

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:31:40.227547Z

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.

Pith citing papers

Observation c63c633b-6f82-49b2-8ac2-495ba396f9b1 · inbound

A Survey on Generative Recommendation: Data, Model, and Tasks cites this paper.

A Survey on Generative Recommendation: Data, Model, and Tasks Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 236

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:50:52.006627Z

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 c4006421-143f-4249-91f7-446dfd205180 · inbound

User Simulator-Guided Multi-Turn Preference Optimization for Reasoning LLM-based Conversational Recommendation cites this paper.

User Simulator-Guided Multi-Turn Preference Optimization for Reasoning LLM-based Conversational Recommendation Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:28:02.567678Z

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 4508cacf-2be4-4e3e-816c-9c38acd14059 · inbound

Factorized Latent Reasoning for LLM-based Recommendation cites this paper.

Factorized Latent Reasoning for LLM-based Recommendation Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:21:25.763329Z

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 d6439a01-fe55-4fc1-9f39-b5726430d388 · inbound

Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces cites this paper.

Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:05:03.748072Z

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 96b5f854-b73b-4e82-a2f7-35b79136e00b · inbound

From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation cites this paper.

From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-01T01:28:22.786837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d70ffb8e-3a23-4ad1-bde1-6675ee936498 · inbound

Think2Go: Generative Next POI Recommendation with LLM Reasoning cites this paper.

Think2Go: Generative Next POI Recommendation with LLM Reasoning Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T15:48:03.628195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e936b29-4134-4de2-809f-1c618ef1173d · inbound

From Prompting to Behavioral Alignment: Personalized LLM Judges for Recommendation Evaluation cites this paper.

From Prompting to Behavioral Alignment: Personalized LLM Judges for Recommendation Evaluation Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T14:17:36.434120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f49bb029-e590-4678-98b5-e2d5c7662bcc · inbound

Learning from Online User Feedback for Shopping Agents cites this paper.

Learning from Online User Feedback for Shopping Agents Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T00:38:07.504889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.