Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals | Paper Citation Record

Observation 0b75aa3c-c4d3-47c5-9a28-9624fa3b0c98 · outbound

This paper cites GPT-4 Technical Report.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals GPT-4 Technical Report

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This paper cites A General Language Assistant as a Laboratory for Alignment.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals A General Language Assistant as a Laboratory for Alignment

Reference 2

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

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 3

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Language models are few-shot learners

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This paper cites Modeling individual preference evolution and choice in a dynamic group setting.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Modeling individual preference evolution and choice in a dynamic group setting

Reference 5

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This paper cites PAL: Sample- efficient personalized reward modeling for pluralistic alignment.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals PAL: Sample- efficient personalized reward modeling for pluralistic alignment

Reference 6

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Unresolved cited work

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This paper cites Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

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This paper cites Rm-r1: Reward modeling as reasoning, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Rm-r1: Reward modeling as reasoning, 2025

Reference 9

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This paper cites On the Measure of Intelligence.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals On the Measure of Intelligence

Reference 10

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This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 11

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This paper cites Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025

Reference 12

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This paper cites Hierarchical neural story generation.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Hierarchical neural story generation

Reference 13

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This paper cites Children’s learning and transfer of inductive reasoning rules: Studies of proximal development.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Children’s learning and transfer of inductive reasoning rules: Studies of proximal development

Reference 14

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Observation bb31e0cb-429b-4c86-a9d9-d80e76a1de6f · outbound

This paper cites Theodoropoulos, and Neil R.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Theodoropoulos, and Neil R

Reference 15

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This paper cites Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs

Reference 16

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This paper cites Generative adversarial nets.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Generative adversarial nets

Reference 17

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This paper cites A survey on personalized alignment – the missing piece for large language models in real-world applications, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals A survey on personalized alignment – the missing piece for large language models in real-world applications, 2025

Reference 18

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This paper cites AMOR: A recipe for building adaptable modular knowledge agents through process feedback.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals AMOR: A recipe for building adaptable modular knowledge agents through process feedback

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This paper cites Training large language models to reason in a continuous latent space, 2024.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Training large language models to reason in a continuous latent space, 2024

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This paper cites Inductive reasoning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Inductive reasoning

Reference 21

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This paper cites Properties of inductive reasoning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Properties of inductive reasoning

Reference 22

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This paper cites Induction: Processes of inference, learning, and discovery.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Induction: Processes of inference, learning, and discovery

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This paper cites The curious case of neural text degeneration.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals The curious case of neural text degeneration

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This paper cites Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model, 2025

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This paper cites Livecodebench: Holistic and contamination free evaluation of large language models for code.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Livecodebench: Holistic and contamination free evaluation of large language models for code

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This paper cites Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging

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This paper cites Other solutions to nash’s bargaining problem.Econometrica: Journal of the Econometric Society, pages 513–518, 1975.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Other solutions to nash’s bargaining problem.Econometrica: Journal of the Econometric Society, pages 513–518, 1975

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This paper cites Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction

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This paper cites Adam: A Method for Stochastic Optimization.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Adam: A Method for Stochastic Optimization

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This paper cites Cognitive trait modelling: The case of inductive reasoning ability.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Cognitive trait modelling: The case of inductive reasoning ability

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Unresolved cited work

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals ComPO: Community Preferences for Language Model Personalization

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This paper cites Lake, Tomer D.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Lake, Tomer D

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals In-context reinforcement learning with algorithm distillation

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This paper cites Aligning to Thousands of Preferences via System Message Generalization.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Aligning to Thousands of Preferences via System Message Generalization

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This paper cites From 1,000,000 users to every user: Scaling up personalized preference for user-level alignment, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals From 1,000,000 users to every user: Scaling up personalized preference for user-level alignment, 2025

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Let's Verify Step by Step

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals SimPO: Simple Preference Optimization with a Reference-Free Reward

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals The link between deductive reasoning and mathematics

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals The con- ceptARC benchmark: Evaluating understanding and generalization in the ARC domain

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This paper cites User-LLM: Efficient LLM Contextualization with User Embeddings.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals User-LLM: Efficient LLM Contextualization with User Embeddings

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This paper cites Learning and sustaining shared normative systems via bayesian rule induction in markov games.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Learning and sustaining shared normative systems via bayesian rule induction in markov games

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This paper cites Introducing openai o1-preview.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Introducing openai o1-preview

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

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Training language models to follow instructions with human feedback

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This paper cites Vicky Zhao, Lili Qiu, and Jianfeng Gao.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Vicky Zhao, Lili Qiu, and Jianfeng Gao

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This paper cites Understanding and benchmarking artificial intelligence: Openai’s o3 is not agi, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Understanding and benchmarking artificial intelligence: Openai’s o3 is not agi, 2025

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Observation 46fd3c2e-fbc4-4ea4-ae96-ca85e99b6fc1 · outbound

This paper cites Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning

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Observation 950f2f82-c25e-44e2-948e-6db70764dd09 · outbound

This paper cites Phenomenal yet puzzling: Testing inductive reasoning capabilities of language models with hypothesis refinement.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Phenomenal yet puzzling: Testing inductive reasoning capabilities of language models with hypothesis refinement

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Observation 0864cdaf-de2a-404e-b441-a444616e0f65 · outbound

This paper cites Improving language understanding with unsupervised learning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Improving language understanding with unsupervised learning

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

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Direct preference optimization: Your language model is secretly a reward model

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:06.512480Z

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This paper cites Zero: Memory optimiza- tions toward training trillion parameter models.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Zero: Memory optimiza- tions toward training trillion parameter models

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Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Rewarded soups: towards pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:06.332341Z

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This paper cites Gpqa: A graduate-level google-proof q&a benchmark.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Gpqa: A graduate-level google-proof q&a benchmark

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This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

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This paper cites Decoding-Time Language Model Alignment with Multiple Objectives.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Decoding-Time Language Model Alignment with Multiple Objectives

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This paper cites Distributional prefer- ence learning: Understanding and accounting for hidden context in RLHF.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Distributional prefer- ence learning: Understanding and accounting for hidden context in RLHF

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:06.177879Z

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Observation cd663109-7525-4932-8c28-fe99be68ac11 · outbound

This paper cites Scaling LLM test-time com- pute optimally can be more effective than scaling parameters for reasoning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Scaling LLM test-time com- pute optimally can be more effective than scaling parameters for reasoning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:53.640008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67c5a2ee-96c2-407f-ad57-1980dacca223 · outbound

This paper cites Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:53.719189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa2bf167-5ddc-4674-b46c-09b3634b9fb2 · outbound

This paper cites Qwen2.5: A party of foundation models, September 2024.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Qwen2.5: A party of foundation models, September 2024

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:53.795945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11ecffe4-a620-4231-8be1-51d6c00a6814 · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning, March 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Qwq-32b: Embracing the power of reinforcement learning, March 2025

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:53.880000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10d83967-79d4-4179-bd19-dce0728158a8 · outbound

This paper cites Exclusive: Chatgpt traffic slips again for third month in a row.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Exclusive: Chatgpt traffic slips again for third month in a row

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:06.038473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2f820ba2-8716-4731-acbe-f69252fda9fc · outbound

This paper cites Planning in natural language improves llm search for code generation.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Planning in natural language improves llm search for code generation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.907247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 78783d00-d3f1-49e7-9411-7f11f264c6d1 · outbound

This paper cites Hypothesis search: Inductive reasoning with language models.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Hypothesis search: Inductive reasoning with language models

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.766169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b756450d-4919-410e-8cc5-4eab8a0e947f · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Chain-of-thought prompting elicits reasoning in large language models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:54.176227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ebf9801-6f6a-436f-a5c9-a66c6f33a0c7 · outbound

This paper cites Codeplan: Unlocking reasoning potential in large language models by scaling code-form planning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Codeplan: Unlocking reasoning potential in large language models by scaling code-form planning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:54.248525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51a7f026-9303-4a49-a549-9ca99a899709 · outbound

This paper cites Fung, Cheng Qian, Jeonghwan Kim, Dilek Hakkani-Tur, and Heng Ji.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Fung, Cheng Qian, Jeonghwan Kim, Dilek Hakkani-Tur, and Heng Ji

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.638599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c3e4865e-913d-4711-8518-6079b8a73970 · outbound

This paper cites Beyond goldfish memory: Long-term open- domain conversation.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Beyond goldfish memory: Long-term open- domain conversation

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.490365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation adc3b117-dd43-493a-a087-3d8b8990d65e · outbound

This paper cites Mir-bench: Benchmarking llm’s long-context intelligence via many-shot in-context inductive reasoning.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Mir-bench: Benchmarking llm’s long-context intelligence via many-shot in-context inductive reasoning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.356626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4780093c-665f-445f-8221-c21c7f022a04 · outbound

This paper cites Qwen3 technical report, 2025.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Qwen3 technical report, 2025

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:54.808948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 550b2658-62e0-4436-b582-512686f546fc · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Tree of thoughts: Deliberate problem solving with large language models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:54.872911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b71ca5b-2ab2-46d5-8779-29b6180e8744 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:54.965005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dac91ccf-7688-4e15-a00a-3f5b11564432 · outbound

This paper cites Rest-mcts*: Llm self-training via process reward guided tree search.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Rest-mcts*: Llm self-training via process reward guided tree search

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.268736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 38e3790d-3238-4b25-b550-de54572b269c · outbound

This paper cites User-centric conversational recommendation: Adapting the need of user with large language models.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals User-centric conversational recommendation: Adapting the need of user with large language models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:05.117334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9a222978-e9b6-401c-b5e6-f3ced4049960 · outbound

This paper cites Personalizing Dialogue Agents: I have a dog, do you have pets too?.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Personalizing Dialogue Agents: I have a dog, do you have pets too?

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:55.172462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c79aea8-f46b-4f21-acc4-c1785b15049e · outbound

This paper cites Do LLMs recognize your preferences? evaluating personalized preference following in LLMs.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Do LLMs recognize your preferences? evaluating personalized preference following in LLMs

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.962047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f4106b1a-9043-4ada-91b0-9b85818f729b · outbound

This paper cites pair-wise comparative feedback.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals pair-wise comparative feedback

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.827620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f93990c1-a057-4805-9ef8-83c49d8f9881 · outbound

This paper cites My girlfriend[22] and I[22] decided to go away somewhat last minute.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals My girlfriend[22] and I[22] decided to go away somewhat last minute

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.702536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fcebfcba-1311-4cd5-ae95-8eab01a3bf4e · outbound

This paper cites oh, I dig this chick.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals oh, I dig this chick

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.567667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c4d52879-8859-41b9-a135-7a8d18f71ec3 · outbound

This paper cites I don't think teenage/20s years are the peak of your life.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals I don't think teenage/20s years are the peak of your life

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.423016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7bad11d5-d6de-4dd2-81fa-334da6fb69ed · outbound

This paper cites inability to keep up with changes.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals inability to keep up with changes

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.257908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ab5e8a2-25f9-4f67-8578-8628e5d34319 · outbound

This paper cites Prefers pragmatic solutions over elaborate suggestions (rejects verbose advice but values empathy).

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Prefers pragmatic solutions over elaborate suggestions (rejects verbose advice but values empathy)

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:04.082369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 787ba9a5-0624-422e-9d5c-057f779bbd5e · outbound

This paper cites Resists reliance on external ad- vice/influences (rejects complex dating tips, favors personal intuition).

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Resists reliance on external ad- vice/influences (rejects complex dating tips, favors personal intuition)

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:03.959186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4acdbb15-2e96-40cb-b0f7-6396ffc1d69c · outbound

This paper cites • Avoidant Conflict Resolution: Tends to sidestep contentious topics (e.g., avoids discussing workplace discrimination head-on except when validating feelings).

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals • Avoidant Conflict Resolution: Tends to sidestep contentious topics (e.g., avoids discussing workplace discrimination head-on except when validating feelings)

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:03.826512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e14e2b5-68c5-4a6b-aa2d-06049d99e557 · outbound

This paper cites • Personal fulfillment tied to overcoming vulnerabilities (mental health improve- ment linked to traveling away for escape).

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals • Personal fulfillment tied to overcoming vulnerabilities (mental health improve- ment linked to traveling away for escape)

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:03.703134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c18f6af-1edf-4406-a7fa-1c29d38f16c0 · outbound

This paper cites people near the border.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals people near the border

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:03.610894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 96dec895-9484-4fad-a65f-b5947c0f8f9c · outbound

This paper cites Thanks, that's nice of you.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Thanks, that's nice of you

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:03.353878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 34bcd7a6-c71c-49fa-80da-5245b251acf4 · outbound

This paper cites un bon gros fdp.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals un bon gros fdp

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:03.126313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c13f8a94-9baf-4b4c-bac4-8d8366621c2d · outbound

This paper cites be sincere.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals be sincere

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:02.928494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation adedf4b0-181d-4253-9975-30d1f0986dfc · outbound

This paper cites Personality Traits Alignment: - Low openness to abstract concepts (preferring straightfor- ward empathy).

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Personality Traits Alignment: - Low openness to abstract concepts (preferring straightfor- ward empathy)

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:02.682047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 42b50d2f-23a9-4e47-bfb8-115ecae99172 · outbound

This paper cites • They often choose to offer comfort, support, and validation to others going through similar struggles, showing empathy and a supportive nature.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals • They often choose to offer comfort, support, and validation to others going through similar struggles, showing empathy and a supportive nature

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:02.532968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d86f1e51-d4e6-47e1-9fa1-3808089fc31f · outbound

This paper cites • They are open to receiving and giving advice, showing a willingness to engage in meaningful conversations that can help others.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals • They are open to receiving and giving advice, showing a willingness to engage in meaningful conversations that can help others

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:02.412565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7ba79cc9-3546-482e-b098-79cf86ea7f9d · outbound

This paper cites They appreciate kind words and genuine responses.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals They appreciate kind words and genuine responses

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:02.288826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a96a7c2d-b548-4968-8f9a-2371f2665e73 · outbound

This paper cites • They are likely to be aware of and respectful of different gender identities and pronouns.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals • They are likely to be aware of and respectful of different gender identities and pronouns

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:02.117689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 077f53f7-9b19-4e46-8d7d-874c7b75c2db · outbound

This paper cites • They seem to be seeking validation and advice on how to navigate relationships, both romantic and platonic.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals • They seem to be seeking validation and advice on how to navigate relationships, both romantic and platonic

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:01.940086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e43ea4cb-c2e0-4b75-bf6a-31f386c78445 · outbound

This paper cites Un bon gros fdp en somme.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Un bon gros fdp en somme

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:01.788787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7f0309b-b468-4771-800f-05d80226a41e · outbound

This paper cites Thanks”, “Sorry.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Thanks”, “Sorry

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:00.669516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 671d10bb-a3d9-48b0-aed4-4c42d573f563 · outbound

This paper cites I live 20 mins.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals I live 20 mins

Reference 102

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:01.564286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1838a208-db0b-437d-bcd6-421229b759cc · outbound

This paper cites an unresolved cited work.

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals Unresolved cited work

Reference 103

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:01.206973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers