1 citations · 1 across the 9 of their papers we have counts for
9 papers
SentGraph: Hierarchical Sentence Graph for Multi-hop Retrieval-Augmented Question Answering
Junli Liang, Pengfei Zhou, Wangqiu Zhou +5
Traditional Retrieval-Augmented Generation (RAG) effectively supports single-hop question answering with large language models but faces significant limitations in multi-hop questi…
EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans
Yingjie Zhou, Xilei Zhu, Siyu Ren +11
Speech-driven Talking Human (TH) generation, commonly known as "Talker," currently faces limitations in multi-subject driving capabilities. Extending this paradigm to "Multi-Talker…
AMO-Bench: Large Language Models Still Struggle in High School Math Competitions
Shengnan An, Xunliang Cai, Xuezhi Cao +8
We present AMO-Bench, an Advanced Mathematical reasoning benchmark with Olympiad level or even higher difficulty, comprising 50 human-crafted problems. Existing benchmarks have wid…
UNO-Bench: A Unified Benchmark for Exploring the Compositional Law Between Uni-modal and Omni-modal in Omni Models
Chen Chen, ZeYang Hu, Fengjiao Chen +6
Multimodal Large Languages models have been progressing from uni-modal understanding toward unifying visual, audio and language modalities, collectively termed omni models. However…
LongCat-Flash Technical Report
Meituan LongCat Team, Bayan, Bei Li +179
We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…
Introducing LongCat-Flash-Thinking: A Technical Report
Meituan LongCat Team, Anchun Gui, Bei Li +122
We present LongCat-Flash-Thinking, an efficient 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model. Its advanced capabilities are cultivated through a metic…
RESCUE: Crowd Evacuation Simulation via Controlling SDM-United Characters
Xiaolin Liu, Tianyi Zhou, Hongbo Kang +6
Crowd evacuation simulation is critical for enhancing public safety, and demanded for realistic virtual environments. Current mainstream evacuation models overlook the complex huma…
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Zhaolu Kang, Junhao Gong, Jiaxu Yan +15
Multimodal Large Language Models (MLLMs) have demonstrated significant potential to advance a broad range of domains. However, current benchmarks for evaluating MLLMs primarily emp…
Audio Turing Test: Benchmarking the Human-likeness of Large Language Model-based Text-to-Speech Systems in Chinese
Xihuai Wang, Ziyi Zhao, Siyu Ren +9
Recent advances in large language models (LLMs) have significantly improved text-to-speech (TTS) systems, enhancing control over speech style, naturalness, and emotional expression…