most citedDynamic Early Exit in Reasoning Models

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Agents' Last Exam

Yiyou Sun, Xinyang Han, Weichen Zhang +355

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…

cs.CL2026

DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection

Junchao Wu, Yefeng Liu, Chenyu Zhu +8

The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misuse. Despite the impressive pe…

cs.CL2025

Marco-Bench-MIF: On Multilingual Instruction-Following Capability of Large Language Models

Bo Zeng, Chenyang Lyu, Sinuo Liu +14

Instruction-following capability has become a major ability to be evaluated for Large Language Models (LLMs). However, existing datasets, such as IFEval, are either predominantly m…

cs.CL2025★ 1 cited

Dynamic Early Exit in Reasoning Models

Chenxu Yang, Qingyi Si, Yongjie Duan +6

Recent advances in large reasoning language models (LRLMs) rely on test-time scaling, which extends long chain-of-thought (CoT) generation to solve complex tasks. However, overthin…

cs.CL2025

Towards Lightweight, Adaptive and Attribute-Aware Multi-Aspect Controllable Text Generation with Large Language Models

Chenyu Zhu, Yefeng Liu, Chenyang Lyu +5

Multi-aspect controllable text generation aims to control text generation in attributes from multiple aspects, making it a complex but powerful task in natural language processing.…