12 citations · 37 across the 28 of their papers we have counts for
16 papers · 1 filter
Mental World Modeling
Hao Fei, Yiran Zhao
World models enable a predictive substrate for planning and action, yet existing formulations merely answer a physical question: what/where it is, and how will it evolve. Human beh…
Higher Satisfaction, Lower Cost: A Technical Report on How LLMs Revolutionize Meituan's Intelligent Interaction Systems
Xuxin Cheng, Ke Zeng, Zhiquan Cao +65
Enhancing customer experience is essential for business success, particularly as service demands grow in scale and complexity. Generative artificial intelligence and Large Language…
MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use
Zijian Wu, Xiangyan Liu, Xinyuan Zhang +12
MCP standardizes how LLMs interact with external systems, forming the foundation for general agents. However, existing MCP benchmarks remain narrow in scope: they focus on read-hea…
The Emergence of Abstract Thought in Large Language Models Beyond Any Language
Yuxin Chen, Yiran Zhao, Yang Zhang +7
As large language models (LLMs) continue to advance, their capacity to function effectively across a diverse range of languages has shown marked improvement. Preliminary studies ob…
Disentangling Language and Culture for Evaluating Multilingual Large Language Models
Jiahao Ying, Wei Tang, Yiran Zhao +3
This paper introduces a Dual Evaluation Framework to comprehensively assess the multilingual capabilities of LLMs. By decomposing the evaluation along the dimensions of linguistic…
The Rise of Parameter Specialization for Knowledge Storage in Large Language Models
Yihuai Hong, Yiran Zhao, Wei Tang +3
Over time, a growing wave of large language models from various series has been introduced to the community. Researchers are striving to maximize the performance of language models…
Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers
Yiran Zhao, Chaoqun Liu, Yue Deng +8
Large language models (LLMs) have revolutionized natural language processing (NLP), yet open-source multilingual LLMs remain scarce, with existing models often limited in language…
Unnatural Languages Are Not Bugs but Features for LLMs
Keyu Duan, Yiran Zhao, Zhili Feng +9
Large Language Models (LLMs) have been observed to process non-human-readable text sequences, such as jailbreak prompts, often viewed as a bug for aligned LLMs. In this work, we pr…
Reasoning Robustness of LLMs to Adversarial Typographical Errors
Esther Gan, Yiran Zhao, Liying Cheng +5
Large Language Models (LLMs) have demonstrated impressive capabilities in reasoning using Chain-of-Thought (CoT) prompting. However, CoT can be biased by users' instruction. In thi…
SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages
Wenxuan Zhang, Hou Pong Chan, Yiran Zhao +9
Large Language Models (LLMs) have shown remarkable abilities across various tasks, yet their development has predominantly centered on high-resource languages like English and Chin…
Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
Chaoqun Liu, Wenxuan Zhang, Yiran Zhao +2
Large language models (LLMs) have demonstrated multilingual capabilities, yet they are mostly English-centric due to the imbalanced training corpora. While prior works have leverag…
Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
Yiran Zhao, Wenyue Zheng, Tianle Cai +4
Safety of Large Language Models (LLMs) has become a critical issue given their rapid progresses. Greedy Coordinate Gradient (GCG) is shown to be effective in constructing adversari…
AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging
Yiran Zhao, Wenxuan Zhang, Huiming Wang +2
As an effective alternative to the direct fine-tuning on target tasks in specific languages, cross-lingual transfer addresses the challenges of limited training data by decoupling…
How do Large Language Models Handle Multilingualism?
Yiran Zhao, Wenxuan Zhang, Guizhen Chen +2
Large language models (LLMs) have demonstrated impressive capabilities across diverse languages. This study explores how LLMs handle multilingualism. Based on observed language rat…
FELM: Benchmarking Factuality Evaluation of Large Language Models
Shiqi Chen, Yiran Zhao, Jinghan Zhang +4
Assessing factuality of text generated by large language models (LLMs) is an emerging yet crucial research area, aimed at alerting users to potential errors and guiding the develop…
Self-Evaluation Guided Beam Search for Reasoning
Yuxi Xie, Kenji Kawaguchi, Yiran Zhao +4
Breaking down a problem into intermediate steps has demonstrated impressive performance in Large Language Model (LLM) reasoning. However, the growth of the reasoning chain introduc…