Learning to Execute Actions or Ask Clarification Questions
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Abstract (arXiv)
Collaborative tasks are ubiquitous activities where a form of communication is required in order to reach a joint goal. Collaborative building is one of such tasks. We wish to develop an intelligent builder agent in a simulated building environment (Minecraft) that can build whatever users wish to build by just talking to the agent. In order to achieve this goal, such agents need to be able to take the initiative by asking clarification questions when further information is needed. Existing works on Minecraft Corpus Dataset only learn to execute instructions neglecting the importance of asking for clarifications. In this paper, we extend the Minecraft Corpus Dataset by annotating all builder utterances into eight types, including clarification questions, and propose a new builder agent model capable of determining when to ask or execute instructions. Experimental results show that our model achieves state-of-the-art performance on the collaborative building task with a substantial improvement. We also define two new tasks, the learning to ask task and the joint learning task. The latter consists of solving both collaborating building and learning to ask tasks jointly.
Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 27 of its 45 references that are in the map. First posted on arXiv 18 Apr 2022.
Builds on
27 of 45 references.
References · 27
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15 more
- 2017Mapping Instructions and Visual Observations to Actions with Reinforcement Learningcited by 80
- 2017Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learningcited by 77
- 2019Executing Instructions in Situated Collaborative Interactionscited by 68
- 2019Just Ask:An Interactive Learning Framework for Vision and Language Navigationcited by 53
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- 2020Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representationscited by 42
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- 2017Learning by Asking Questionscited by 25
- 2017Representation Learning for Grounded Spatial Reasoningcited by 23
- 2022Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Trackingcited by 18
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- 2018Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observationcited by 12
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Citing papers per year: 2022: 1; 2023: 14; 2024: 13; 2025: 1; 2026: 1.
30 papers.
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- 2024Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questionscited by 32
- 2023Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedbackcited by 31
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- 2023"Are you telling me to put glasses on the dog?'' Content-Grounded Annotation of Instruction Clarification Requests in the CoDraw Datasetcited by 3
- 2023Towards a Neural Era in Dialogue Management for Collaboration: A Literature Surveycited by 3
- 2023'What are you referring to?' Evaluating the Ability of Multi-Modal Dialogue Models to Process Clarificational Exchangescited by 3
- 2024Nebula: A discourse aware Minecraft Buildercited by 3
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- 2024ArchCode: Incorporating Software Requirements in Code Generation with Large Language Models2 Aug 2024
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- 2024Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft25 Jun 2024
- 2024Instruction Tuning With Loss Over Instructions23 May 2024
- 2024It Couldn't Help But Overhear: On the Limits of Modelling Meta-Communicative Grounding Acts with Supervised Learning2 May 2024
- 2024Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agents14 Feb 2024
- 2024Large Language Models as Minecraft Agents13 Feb 2024
18 more
- 2024Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questions9 Feb 2024
- 2024Improving Agent Interactions in Virtual Environments with Language Models8 Feb 2024
- 2024Taking Action Towards Graceful Interaction: The Effects of Performing Actions on Modelling Policies for Instruction Clarification Requests30 Jan 2024
- 2023Lexical Entrainment for Conversational Systems14 Oct 2023
- 2023DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning11 Sep 2023
- 2023'What are you referring to?' Evaluating the Ability of Multi-Modal Dialogue Models to Process Clarificational Exchanges28 Jul 2023
- 2023Towards a Neural Era in Dialogue Management for Collaboration: A Literature Survey18 Jul 2023
- 2023Solving Dialogue Grounding Embodied Task in a Simulated Environment using Further Masked Language Modeling21 Jun 2023
- 2023Rethink the Effectiveness of Text Data Augmentation: An Empirical Analysis13 Jun 2023
- 2023"Are you telling me to put glasses on the dog?'' Content-Grounded Annotation of Instruction Clarification Requests in the CoDraw Dataset4 Jun 2023
- 2023Self Contrastive Learning for Session-based Recommendation2 Jun 2023
- 2023R2H: Building Multimodal Navigation Helpers that Respond to Help Requests23 May 2023
- 2023Rethinking Semi-supervised Learning with Language Models22 May 2023
- 2023When and What to Ask Through World States and Text Instructions: IGLU NLP Challenge Solution9 May 2023
- 2023Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner2 May 2023
- 2023Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedback21 Apr 2023
- 2023Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw Dataset28 Feb 2023
- 2022Attention-based Ingredient Phrase Parser5 Oct 2022
- 2024Instruction Tuning With Loss Over Instructionscited by 40
- 2023DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuningcited by 34
- 2024Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questionscited by 32
- 2023Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedbackcited by 31
- 2023Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learnercited by 23
- 2024A Survey of Conversational Searchcited by 22
- 2023Rethinking Semi-supervised Learning with Language Modelscited by 17
- 2023Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw Datasetcited by 11
- 2024ArchCode: Incorporating Software Requirements in Code Generation with Large Language Modelscited by 8
- 2024RAcQUEt: Unveiling the Dangers of Overlooked Referential Ambiguity in Visual LLMscited by 8
- 2023When and What to Ask Through World States and Text Instructions: IGLU NLP Challenge Solutioncited by 5
- 2023R2H: Building Multimodal Navigation Helpers that Respond to Help Requestscited by 5
12 most cited of 24 All 24 (JSON)
- 2026Beyond Local Surprise: Grounded Dialogue as Selective Belief Revision under Referential Uncertainty26 Aug 2026
- 2025It Depends: Resolving Referential Ambiguity in Minimal Contexts with Commonsense Knowledge19 Sep 2025
- 2024RAcQUEt: Unveiling the Dangers of Overlooked Referential Ambiguity in Visual LLMs18 Dec 2024
- 2024A Survey of Conversational Search21 Oct 2024
- 2024ArchCode: Incorporating Software Requirements in Code Generation with Large Language Models2 Aug 2024
- 2024Nebula: A discourse aware Minecraft Builder26 Jun 2024
- 2024Instruction Tuning With Loss Over Instructions23 May 2024
- 2024It Couldn't Help But Overhear: On the Limits of Modelling Meta-Communicative Grounding Acts with Supervised Learning2 May 2024
- 2024Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questions9 Feb 2024
- 2024Taking Action Towards Graceful Interaction: The Effects of Performing Actions on Modelling Policies for Instruction Clarification Requests30 Jan 2024
- 2023Lexical Entrainment for Conversational Systems14 Oct 2023
- 2023DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning11 Sep 2023
12 newest of 24 All 24 (JSON)