mlsanityData to 14 Oct 2026

AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence

arXiv 2404.11826 ↗First posted 18 Apr 2024cs.CLcited by 12

Not on the map. Why?

Abstract (arXiv)

As the integration of large language models into daily life is on the rise, there is a clear gap in benchmarks for advising on subjective and personal dilemmas. To address this, we introduce AdvisorQA, the first benchmark developed to assess LLMs' capability in offering advice for deeply personalized concerns, utilizing the LifeProTips subreddit forum. This forum features a dynamic interaction where users post advice-seeking questions, receiving an average of 8.9 advice per query, with 164.2 upvotes from hundreds of users, embodying a collective intelligence framework. Therefore, we've completed a benchmark encompassing daily life questions, diverse corresponding responses, and majority vote ranking to train our helpfulness metric. Baseline experiments validate the efficacy of AdvisorQA through our helpfulness metric, GPT-4, and human evaluation, analyzing phenomena beyond the trade-off between helpfulness and harmlessness. AdvisorQA marks a significant leap in enhancing QA systems for providing personalized, empathetic advice, showcasing LLMs' improved understanding of human subjectivity.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 42 of its 82 references that are in the map. First posted on arXiv 18 Apr 2024.

Builds on

42 of 82 references.

References · 42

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  4. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  5. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  6. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  7. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  8. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
  9. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  10. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  11. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
  12. 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scalingcited by 1,786
30 more
  1. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,252
  2. 2020StereoSet: Measuring stereotypical bias in pretrained language modelscited by 924
  3. 2023Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedbackcited by 759
  4. 2020Aligning AI With Shared Human Valuescited by 723
  5. 2021BARTScore: Evaluating Generated Text as Text Generationcited by 722
  6. 2021P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Taskscited by 689
  7. 2019ELI5: Long Form Question Answeringcited by 575
  8. 2024RewardBench: Evaluating Reward Models for Language Modelingcited by 499
  9. 2018Texygen: A Benchmarking Platform for Text Generation Modelscited by 491
  10. 2021DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Expertscited by 441
  11. 2023Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Mergingcited by 280
  12. 2023LEVER: Learning to Verify Language-to-Code Generation with Executioncited by 239
  13. 2023FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Setscited by 201
  14. 2021Hurdles to Progress in Long-form Question Answeringcited by 167
  15. 2013A Theoretical Analysis of NDCG Type Ranking Measurescited by 119
  16. 2023A Critical Evaluation of Evaluations for Long-form Question Answeringcited by 111
  17. 2023When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Taskscited by 90
  18. 2023Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Modelcited by 79
  19. 2020Dialogue Response Ranking Training with Large-Scale Human Feedback Datacited by 68
  20. 2024A Computational Framework for Behavioral Assessment of LLM Therapistscited by 62
  21. 2023The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Valuescited by 54
  22. 2022Critic-Guided Decoding for Controlled Text Generationcited by 45
  23. 2022A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Predictioncited by 44
  24. 2017Argument Mining with Structured SVMs and RNNscited by 37
  25. 2023Compositional preference models for aligning LMscited by 26
  26. 2020SubjQA: A Dataset for Subjectivity and Review Comprehensioncited by 24
  27. 2023KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Applicationcited by 24
  28. 2023LifeTox: Unveiling Implicit Toxicity in Life Advicecited by 14
  29. 2023Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learningcited by 7
  30. 2020Help! Need Advice on Identifying Advicecited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 4; 2026: 5.

12 papers.

  1. 2025ELEPHANT: Measuring and understanding social sycophancy in LLMscited by 129
  2. 2024SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMscited by 57
  3. 2024Are LLM-Judges Robust to Expressions of Uncertainty? Investigating the effect of Epistemic Markers on LLM-based Evaluationcited by 29
  4. 2026CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attributioncited by 14
  5. 2025Drift: Decoding-time Personalized Alignments with Implicit User Preferencescited by 13
  6. 2024Guaranteed Generation from Large Language Modelscited by 7
  7. 2025Sycophantic AI Decreases Prosocial Intentions and Promotes Dependencecited by 6
  8. 2025IP-Dialog: Evaluating Implicit Personalization in Dialogue Systems with Synthetic Datacited by 1
  9. 2026DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deferencecited by 1
  10. 2026Pro-AI Bias in Large Language Modelscited by 0
  11. 2026Micro Language Models Enable Instant Responsescited by 0
  12. 2026BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contextscited by 0