activity
20232026
most citedTencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs

2 citations · 3 across the 12 of their papers we have counts for

collaborators

13 papers

cs.AI2026

DramaChain Bench: An End-to-End Benchmark for Short-Drama Generation

Haoyuan Shi, Mingtao Chen, Shuo Jiang +12

Commercial short-drama production follows a multi-stage chain: script, storyboard, keyframe imagery, shot-level video, and the finished short drama. Most existing benchmarks evalua…

cs.AI2026

TRAJDEBUG: Tracing Error Lifecycle to Identify Critical Failures in Long-Horizon Agent Trajectories

Yunjia Qi, Zehua Yin, Xintong Shi +10

LLM-based agentic systems have shown remarkable capabilities in complex domains, while suffering from cascading errors and difficulty in debugging. Critical error detection aims to…

cs.SE2026

RepoProbe: Benchmarking Architecture-Aware Repository Comprehension with Checklists

Yuexi Yang, Alyssa Wu, Ji Luo +4

The integration of Large Language Models (LLMs) into software engineering has shifted the focus from function-level generation to repository-scale assistance. However, existing ben…

cs.CL2026

Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?

Yangda Peng, Yunjia Qi, Haotian Xia +8

Rubric-based scoring has become a widely used paradigm in model evaluation, typically with LLM-as-a-Judge (LaaJ) for rubric scoring. However, the reliability of LaaJ for rubric sco…

cs.CV2026

ETCHR: Editing To Clarify and Harness Reasoning

Beichen Zhang, Yuhong Liu, Jinsong Li +3

Multimodal Large Language Models have advanced visual reasoning, yet a purely textual chain of thought remains a bottleneck for questions that require fine-grained focus or view tr…

cs.SE2026

SWE-Milestone: Evaluating AI Agents on Continuous Software Evolution

Gangda Deng, Zhaoling Chen, Zhongming Yu +11

Real-world software must continuously evolve to meet ever-changing and open-ended requirements. AI agents, increasingly deployed as long-running systems, are now entrusted to drive…

cs.CV2026

EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models

Xuanlang Dai, Yujie Zhou, Long Xing +6

Recently, Multimodal Large Language Models (MLLMs) have been widely integrated into diffusion frameworks primarily as text encoders to tackle complex tasks such as spatial reasonin…

cs.CL2026

UltraLogic: Enhancing LLM Reasoning through Large-Scale Data Synthesis and Bipolar Float Reward

Yile Liu, Yixian Liu, Zongwei Li +7

While Large Language Models (LLMs) have demonstrated significant potential in natural language processing , complex general-purpose reasoning requiring multi-step logic, planning,…

cs.CL2026

EternalMath: A Living Benchmark of Frontier Mathematics that Evolves with Human Discovery

Jicheng Ma, Guohua Wang, Xinhua Feng +3

Current evaluations of mathematical reasoning in large language models (LLMs) are dominated by static benchmarks, either derived from competition-style problems or curated through…

cs.CV2025

Q-Save: Towards Scoring and Attribution for Generated Video Evaluation

Xiele Wu, Zicheng Zhang, Mingtao Chen +12

Evaluating AI-generated video (AIGV) quality hinges on three crucial dimensions: visual quality, dynamic quality, and text-video alignment. While numerous evaluation datasets and a…

cs.CL2024

IDGen: Item Discrimination Induced Prompt Generation for LLM Evaluation

Fan Lin, Shuyi Xie, Yong Dai +7

As Large Language Models (LLMs) grow increasingly adept at managing complex tasks, the evaluation set must keep pace with these advancements to ensure it remains sufficiently discr…

cs.CV2024★ 1 cited

Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

Zhimin Li, Jianwei Zhang, Qin Lin +42

We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transfo…

cs.CL2023★ 2 cited

TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs

Shuyi Xie, Wenlin Yao, Yong Dai +11

Large language models (LLMs) have shown impressive capabilities across various natural language tasks. However, evaluating their alignment with human preferences remains a challeng…