18 citations · 27 across the 42 of their papers we have counts for
11 papers · 1 filter
HiMPO: Hindsight-Informed Memory Policy Optimization for Less-Entangled Credit in Long-Horizon Agents
Jiangze Yan, Yi Shen, Wenjing Zhang +6
Long-horizon agents compress interaction histories into memory, but final outcomes entangle memory-writing credit with tool failures and reasoning errors. We propose HiMPO, a Hinds…
Mixture of Heterogeneous Grouped Experts for Language Modeling
Zhicheng Ma, Xiang Liu, Zhaoxiang Liu +5
Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficiently. However, standard MoEs enf…
Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs
Xiaoran Liu, Yuerong Song, Zhigeng Liu +6
Rotary Position Embeddings (RoPE) have become a standard for encoding sequence order in Large Language Models (LLMs) by applying rotations to query and key vectors in the complex p…
Sparser Block-Sparse Attention via Token Permutation
Xinghao Wang, Pengyu Wang, Dong Zhang +7
Scaling the context length of large language models (LLMs) offers significant benefits but is computationally expensive. This expense stems primarily from the self-attention mechan…
Fuzzy Reasoning Chain (FRC): An Innovative Reasoning Framework from Fuzziness to Clarity
Ping Chen, Xiang Liu, Zhaoxiang Liu +7
With the rapid advancement of large language models (LLMs), natural language processing (NLP) has achieved remarkable progress. Nonetheless, significant challenges remain in handli…
SLearnLLM: A Self-Learning Framework for Efficient Domain-Specific Adaptation of Large Language Models
Xiang Liu, Zhaoxiang Liu, Peng Wang +4
When using supervised fine-tuning (SFT) to adapt large language models (LLMs) to specific domains, a significant challenge arises: should we use the entire SFT dataset for fine-tun…
Safety Evaluation and Enhancement of DeepSeek Models in Chinese Contexts
Wenjing Zhang, Xuejiao Lei, Zhaoxiang Liu +11
DeepSeek-R1, renowned for its exceptional reasoning capabilities and open-source strategy, is significantly influencing the global artificial intelligence landscape. However, it ex…
Safety Evaluation of DeepSeek Models in Chinese Contexts
Wenjing Zhang, Xuejiao Lei, Zhaoxiang Liu +8
Recently, the DeepSeek series of models, leveraging their exceptional reasoning capabilities and open-source strategy, is reshaping the global AI landscape. Despite these advantage…
Methodology of Adapting Large English Language Models for Specific Cultural Contexts
Wenjing Zhang, Siqi Xiao, Xuejiao Lei +7
The rapid growth of large language models(LLMs) has emerged as a prominent trend in the field of artificial intelligence. However, current state-of-the-art LLMs are predominantly b…
What is the best model? Application-driven Evaluation for Large Language Models
Shiguo Lian, Kaikai Zhao, Xinhui Liu +5
General large language models enhanced with supervised fine-tuning and reinforcement learning from human feedback are increasingly popular in academia and industry as they generali…
CHiSafetyBench: A Chinese Hierarchical Safety Benchmark for Large Language Models
Wenjing Zhang, Xuejiao Lei, Zhaoxiang Liu +5
With the profound development of large language models(LLMs), their safety concerns have garnered increasing attention. However, there is a scarcity of Chinese safety benchmarks fo…