1 citations · 2 across the 10 of their papers we have counts for
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Closing the Verification Loop: Self-Check Captioning for Long-Paragraph Detailed Audio Captioning
Fengji Ma, Yan Rong, Xu Li +3
Long-paragraph detailed audio captioning, which requires dense and transcript-faithful descriptions of fine-grained audio content, remains unsolved for current audio-visual multimo…
ACE-Cap: Active Evidence Acquisition via Agentic Co-Evolution for Long-Paragraph Fine-Grained Audio Captioning
Fengji Ma, Yan Rong, Xu Li +3
Long-paragraph fine-grained audio captioning requires models to recover diverse acoustic facts while avoiding omissions and unsupported details. However, prevailing captioners rema…
AudioMap: Cloze-and-Choice Reinforcement Learning for Time-Aware Dense Audio Captioning
Yan Rong, Fengji Ma, Xu Li +3
Time-aware dense audio captioning (TDAC) aims to generate multiple fine-grained attributes (dense) of the audio with precise time boundaries (time-aware). Existing methods struggle…
AudioScape-TTA: A Structured Soundscape Benchmark for Fine-Grained Text-to-Audio Evaluation
Jinting Wang, Yuguang Yang, Shengyu Li +4
Text-to-audio (TTA) generation has recently achieved remarkable progress in synthesizing realistic audio from natural language descriptions. However, determining whether generated…
Audio-DeepThinker: Progressive Reasoning-Aware Reinforcement Learning for High-Quality Chain-of-Thought Emergence in Audio Language Models
Xiang He, Chenxing Li, Jinting Wang +5
Large Audio-Language Models (LALMs) have made significant progress in audio understanding, yet they primarily operate as perception-and-answer systems without explicit reasoning pr…