13 citations · 22 across the 22 of their papers we have counts for
11 papers · 1 filter
Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks
Chuyifei Zhang, Hongyu Cui, Xiaowen Huang +1
Position-controlled evaluation is standard for retrieval tasks such as Needle-in-a-Haystack and RULER, but mainstream reasoning benchmarks do not control positional placement of ta…
Taming the Thinker: Conditional Entropy Shaping for Adaptive LLM Reasoning
Shuyu Wei, Jian Sun, Delai Qiu +6
Entropy-based deep reasoning has emerged as a promising direction for improving the reasoning capabilities of Large Language Models (LLMs), but existing methods often either increa…
Mobile-Agent-V: A Video-Guided Approach for Effortless and Efficient Operational Knowledge Injection in Mobile Automation
Junyang Wang, Haiyang Xu, Xi Zhang +4
The exponential rise in mobile device usage necessitates streamlined automation for effective task management, yet many AI frameworks fall short due to inadequate operational exper…
Don't Command, Cultivate: An Exploratory Study of System-2 Alignment
Yuhang Wang, Yuxiang Zhang, Yanxu Zhu +2
The o1 system card identifies the o1 models as the most robust within OpenAI, with their defining characteristic being the progression from rapid, intuitive thinking to slower, mor…
ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models
Yahan Tu, Rui Hu, Jitao Sang
Hallucination poses a persistent challenge for multimodal large language models (MLLMs). However, existing benchmarks for evaluating hallucinations are generally static, which may…
KG-FPQ: Evaluating Factuality Hallucination in LLMs with Knowledge Graph-based False Premise Questions
Yanxu Zhu, Jinlin Xiao, Yuhang Wang +1
Recent studies have demonstrated that large language models (LLMs) are susceptible to being misled by false premise questions (FPQs), leading to errors in factual knowledge, know a…
Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration
Junyang Wang, Haiyang Xu, Haitao Jia +6
Mobile device operation tasks are increasingly becoming a popular multi-modal AI application scenario. Current Multi-modal Large Language Models (MLLMs), constrained by their train…
Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning
Jitao Sang, Yuhang Wang, Jing Zhang +5
This paper presents a follow-up study to OpenAI's recent superalignment work on Weak-to-Strong Generalization (W2SG). Superalignment focuses on ensuring that high-level AI systems…
Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception
Junyang Wang, Haiyang Xu, Jiabo Ye +5
Mobile device agent based on Multimodal Large Language Models (MLLM) is becoming a popular application. In this paper, we introduce Mobile-Agent, an autonomous multi-modal mobile d…
CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models
Yuhang Wang, Yanxu Zhu, Chao Kong +4
As the scaling of Large Language Models (LLMs) has dramatically enhanced their capabilities, there has been a growing focus on the alignment problem to ensure their responsible and…
AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation
Junyang Wang, Yuhang Wang, Guohai Xu +8
Despite making significant progress in multi-modal tasks, current Multi-modal Large Language Models (MLLMs) encounter the significant challenge of hallucinations, which may lead to…