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cs.CL2026

Scaling Latent Reasoning via Looped Language Models

Rui-Jie Zhu, Zixuan Wang, Kai Hua +30

Modern LLMs are trained to "think" primarily via explicit text generation, such as chain-of-thought (CoT), which defers reasoning to post-training and under-leverages pre-training…

cs.CL2026

HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

Xintao Wang, Jian Yang, Weiyuan Li +8

Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Langu…

cs.CL2026

Towards Fair and Comprehensive Evaluation of Routers in Collaborative LLM Systems

Wanxing Wu, He Zhu, Yixia Li +7

Large language models (LLMs) have achieved success, but cost and privacy constraints necessitate deploying smaller models locally while offloading complex queries to cloud-based mo…

cs.CL2026

BiasScope: Towards Automated Detection of Bias in LLM-as-a-Judge Evaluation

Peng Lai, Zhihao Ou, Yong Wang +4

LLM-as-a-Judge has been widely adopted across various research and practical applications, yet the robustness and reliability of its evaluation remain a critical issue. A core chal…

cs.CL2026

They Said Memes Were Harmless-We Found the Ones That Hurt: Decoding Jokes, Symbols, and Cultural References

Sahil Tripathi, Gautam Siddharth Kashyap, Mehwish Nasim +3

Meme-based social abuse detection is challenging because harmful intent often relies on implicit cultural symbolism and subtle cross-modal incongruence. Prior approaches, from fusi…

cs.CL2025

OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Siming Huang, Tianhao Cheng, J. K. Liu +16

Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning tasks and agent systems. While open-access code LLMs are in…