5 papers · 1 filter
GRC: Unifying Reasoning-Driven Generation, Retrieval and Compression
Zhongtao Miao, Qiyu Wu, Yoshimasa Tsuruoka
Text embedding and generative tasks are usually trained separately based on large language models (LLMs) nowadays. This causes a large amount of training cost and deployment effort…
MusTBench: Benchmarking and Advancing Temporal Grounding in Music LLMs
Daeyong Kwon, Qiyu Wu, Shinobu Kuriya +6
Recent Large Audio-Language Models (LALMs) have demonstrated promising abilities in understanding musical content. However, whether their responses are grounded in the correct temp…
Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations
Shaomu Tan, Ryosuke Mitani, Ritvik Choudhary +3
Over the years, automatic MT metrics have hillclimbed benchmarks and presented strong and sometimes human-level agreement with human ratings. Yet they remain black-box, offering li…
MCA: Modality Composition Awareness for Robust Composed Multimodal Retrieval
Qiyu Wu, Shuyang Cui, Satoshi Hayakawa +3
Multimodal retrieval, which seeks to retrieve relevant content across modalities such as text or image, supports applications from AI search to contents production. Despite the suc…
From Chaos to Order: The Atomic Reasoner Framework for Fine-grained Reasoning in Large Language Models
Jinyi Liu, Yan Zheng, Rong Cheng +8
Recent advances in large language models (LLMs) have shown remarkable progress, yet their capacity for logical ``slow-thinking'' reasoning persists as a critical research frontier.…