VisInteract: Towards Dynamic Interactive Text-to-Visualization under Imperfect Queries

arXiv:2609.15182 · cs.AI · Submitted 2026-09-14 · Read on arXiv

cs.AI

Submitted: 2026-09-14

Updated: 2026-09-14

Code: https://github.com/wxxv/VisInteract

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 33× in this paper · explained in 2 episodes
• Aggregation — 18× in this paper · explained in 1 episode
• Alignment — 7× in this paper · explained in 1 episode
• Fidelity — 6× in this paper · explained in 2 episodes
• Monte Carlo Tree Search — 6× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Action Space — 4× in this paper · explained in 1 episode
• Credit assignment — 4× in this paper · explained in 3 episodes
• Text-to-SQL — 3× in this paper · explained in 3 episodes
• Aggregation Function — 2× in this paper · explained in 1 episode
• Alignment Dimensions — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Analyzer — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Multi-Agent System — 1× in this paper · explained in 5 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Semantic Drift — 1× in this paper · explained in 3 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• World Model — 1× in this paper · explained in 7 episodes
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• MultiVis-Agent: A Multi-Agent Framework with Logic Rules for Reliable and Comprehensive Cross-Modal Data Visualization
• G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
• Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B

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