5 citations · 15 across the 14 of their papers we have counts for
14 papers
UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Haoming Wang, Haoyang Zou, Huatong Song +109
The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…
Acting Less is Reasoning More! Teaching Model to Act Efficiently
Hongru Wang, Cheng Qian, Wanjun Zhong +7
Tool-integrated reasoning (TIR) augments large language models (LLMs) with the ability to invoke external tools during long-form reasoning, such as search engines and code interpre…
Self-Reasoning Language Models: Unfold Hidden Reasoning Chains with Few Reasoning Catalyst
Hongru Wang, Deng Cai, Wanjun Zhong +4
Inference-time scaling has attracted much attention which significantly enhance the performance of Large Language Models (LLMs) in complex reasoning tasks by increasing the length…
AdaCtrl: Towards Adaptive and Controllable Reasoning via Difficulty-Aware Budgeting
Shijue Huang, Hongru Wang, Wanjun Zhong +4
Modern large reasoning models demonstrate impressive problem-solving capabilities by employing sophisticated reasoning strategies. However, they often struggle to balance efficienc…
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Jiazhan Feng, Shijue Huang, Xingwei Qu +6
While reasoning models (e.g., DeepSeek R1) trained with reinforcement learning (RL), excel in textual reasoning, they struggle in scenarios requiring structured problem-solving, su…
UI-TARS: Pioneering Automated GUI Interaction with Native Agents
Yujia Qin, Yining Ye, Junjie Fang +32
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., keyboard and mouse operations). U…
Towards Real-World Stickers Use: A New Dataset for Multi-Tag Sticker Recognition
Bingbing Wang, Bin Liang, Chun-Mei Feng +6
In real-world conversations, the diversity and ambiguity of stickers often lead to varied interpretations based on the context, necessitating the requirement for comprehensively un…
CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models
Zexuan Qiu, Jingjing Li, Shijue Huang +3
Developing Large Language Models (LLMs) with robust long-context capabilities has been the recent research focus, resulting in the emergence of long-context LLMs proficient in Chin…
Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios
Shijue Huang, Wanjun Zhong, Jianqiao Lu +10
The recent trend of using Large Language Models (LLMs) as tool agents in real-world applications underscores the necessity for comprehensive evaluations of their capabilities, part…
SDIF-DA: A Shallow-to-Deep Interaction Framework with Data Augmentation for Multi-modal Intent Detection
Shijue Huang, Libo Qin, Bingbing Wang +2
Multi-modal intent detection aims to utilize various modalities to understand the user's intentions, which is essential for the deployment of dialogue systems in real-world scenari…
Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages
Libo Qin, Qiguang Chen, Fuxuan Wei +2
Chain-of-thought (CoT) is capable of eliciting models to explicitly generate reasoning paths, thus promoting reasoning accuracy and attracting increasing attention. Specifically, z…
Improving Few-shot and Zero-shot Entity Linking with Coarse-to-Fine Lexicon-based Retriever
Shijue Huang, Bingbing Wang, Libo Qin +2
Few-shot and zero-shot entity linking focus on the tail and emerging entities, which are more challenging but closer to real-world scenarios. The mainstream method is the ''retriev…
MMSD2.0: Towards a Reliable Multi-modal Sarcasm Detection System
Libo Qin, Shijue Huang, Qiguang Chen +5
Multi-modal sarcasm detection has attracted much recent attention. Nevertheless, the existing benchmark (MMSD) has some shortcomings that hinder the development of reliable multi-m…
Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System
Libo Qin, Tianbao Xie, Shijue Huang +3
Consistency Identification has obtained remarkable success on open-domain dialogue, which can be used for preventing inconsistent response generation. However, in contrast to the r…