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20242026
most citedEvaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis

2 citations · 2 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CL2025

Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning

Yihong Tang, Kehai Chen, Muyun Yang +4

The advancement of Large Language Models (LLMs) has spurred significant interest in Role-Playing Agents (RPAs) for applications such as emotional companionship and virtual interact…

cs.CL2025

Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory

Hongli Zhou, Hui Huang, Ziqing Zhao +10

The evaluation of large language models (LLMs) via benchmarks is widespread, yet inconsistencies between different leaderboards and poor separability among top models raise concern…

cs.CL2025

DuplexMamba: Enhancing Real-time Speech Conversations with Duplex and Streaming Capabilities

Xiangyu Lu, Wang Xu, Haoyu Wang +5

Real-time speech conversation is essential for natural and efficient human-machine interactions, requiring duplex and streaming capabilities. Traditional Transformer-based conversa…

cs.CL2025

Memory-augmented Query Reconstruction for LLM-based Knowledge Graph Reasoning

Mufan Xu, Gewen Liang, Kehai Chen +5

Large language models (LLMs) have achieved remarkable performance on knowledge graph question answering (KGQA) tasks by planning and interacting with knowledge graphs. However, exi…

cs.CL2025★ 2 cited

Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis

Andong Chen, Yuchen Song, Wenxin Zhu +4

The o1-Like LLMs are transforming AI by simulating human cognitive processes, but their performance in multilingual machine translation (MMT) remains underexplored. This study exam…

cs.CL2025

MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training

Hui Huang, Jiaheng Liu, Yancheng He +5

Complex instruction-following with elaborate constraints is imperative for Large Language Models (LLMs). While existing methods have constructed data for complex instruction alignm…