2 citations · 2 across the 28 of their papers we have counts for
29 papers
LongEmo: Towards Emotion Understanding and Reasoning in Long Videos
Shuo Zhang, Yifan Zhou, Han Wang +15
While recent Multimodal Large Language Models (MLLMs) have shown promise in affective computing, their reasoning capabilities are largely confined to short video clips with limited…
Explicit Representation Alignment for Multimodal Sentiment Analysis
Baode Wang, Ziming Wang, Huacan Wang +2
Multimodal affective analysis aims to understand human sentiment and emotion by jointly modeling heterogeneous modalities such as text and images. However, multimodal models often…
SMH-Bench: Benchmarking LLM Agents for Environment-Grounded Reasoning and Action in Smart Homes
Kuan Li, Shuo Zhang, Huacan Wang +12
Smart homes are evolving toward complex state-dependent living environments, requiring Large Language Models (LLMs) to reason over user intent, preferences, and multi-device intera…
HomeFlow: A Data Flywheel for Smart Home Agent Training with Verifiable Simulation
Yi Gu, Huacan Wang, Shuo Zhang +10
Large language model agents are moving beyond text-only interaction toward physical-world control, with smart homes as a representative domain. Real domestic interaction requires u…
VaaWIT: Visual-Aware Adaptation of Large Language Models for Multilingual Web Image Translation
Bo Li, Ronghao Chen, Ningyuan Deng +3
Translating text embedded in Web images is crucial for improving content accessibility and cross-lingual information retrieval, particularly within social media and e-commerce doma…
SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents
Yifan Zhou, Zhentao Zhang, Ziming Cheng +8
As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether they can generate correct, re…
On the Role of Language Representations in Auto-Bidding: Findings and Implications
Guanyu Zhu, Jining Luan, Hanwen Du +11
Auto-bidding is a crucial task in real-time advertising markets, where policies must optimize long-horizon value under delivery constraints (e.g., budget and CPA). Existing methods…
UIPress: Bringing Optical Token Compression to UI-to-Code Generation
Dasen Dai, Shuoqi Li, Ronghao Chen +3
UI-to-Code generation requires vision-language models (VLMs) to produce thousands of tokens of structured HTML/CSS from a single screenshot, making visual token efficiency critical…
FlashSign: Pose-Free Guidance for Efficient Sign Language Video Generation
Liuzhou Zhang, Zeyu Zhang, Biao Wu +10
Sign language plays a crucial role in bridging communication gaps between the deaf and hard-of-hearing communities. However, existing sign language video generation models often re…
EpochX: Building the Infrastructure for an Emergent Agent Civilization
Huacan Wang, Chaofa Yuan, Xialie Zhuang +15
General-purpose technologies reshape economies less by improving individual tools than by enabling new ways to organize production and coordination. We believe AI agents are approa…
Chain of Mindset: Reasoning with Adaptive Cognitive Modes
Tianyi Jiang, Arctanx An, Hengyi Feng +12
Human problem-solving is never the repetition of a single mindset, by which we mean a distinct mode of cognitive processing. When tackling a specific task, we do not rely on a sing…
Where and How to Prune: An Empirical Study of Visual Token Pruning for GUI Agent Navigation
Daiqiang Li, Zihao Pan, Zeyu Zhang +8
In recent years, GUI agents have demonstrated strong potential in navigation tasks. However, preserving complete historical screenshots introduces substantial computational overhea…
Controlled Self-Evolution for Algorithmic Code Optimization
Tu Hu, Ronghao Chen, Shuo Zhang +9
Self-evolution methods enhance code generation through iterative "generate-verify-refine" cycles, yet existing approaches suffer from low exploration efficiency, failing to discove…
Does Memory Need Graphs? A Unified Framework and Empirical Analysis for Long-Term Dialog Memory
Sen Hu, Yuxiang Wei, Jiaxin Ran +5
Graph structures are increasingly used in dialog memory systems, but empirical findings on their effectiveness remain inconsistent, making it unclear which design choices truly mat…
EvoFSM: Controllable Self-Evolution for Deep Research with Finite State Machines
Shuo Zhang, Chaofa Yuan, Ryan Guo +11
While LLM-based agents have shown promise for deep research, most existing approaches rely on fixed workflows that struggle to adapt to real-world, open-ended queries. Recent work…
QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining
Jun Han, Shuo Zhang, Wei Li +14
Financial markets are noisy and non-stationary, making alpha mining highly sensitive to backtest noise and regime shifts. While recent agentic frameworks improve automation, they o…
MemGovern: Enhancing Code Agents through Learning from Governed Human Experiences
Qihao Wang, Ziming Cheng, Shuo Zhang +12
While autonomous software engineering (SWE) agents are reshaping programming paradigms, they currently suffer from a "closed-world" limitation: they attempt to fix bugs from scratc…
CloneMem: Benchmarking Long-Term Memory for AI Clones
Sen Hu, Zhiyu Zhang, Yuxiang Wei +4
AI Clones aim to simulate an individual's thoughts and behaviors to enable long-term, personalized interaction, placing stringent demands on memory systems to model experiences, em…
RealMem: Benchmarking LLMs in Real-World Memory-Driven Interaction
Haonan Bian, Zhiyuan Yao, Sen Hu +7
As Large Language Models (LLMs) evolve from static dialogue interfaces to autonomous general agents, effective memory is paramount to ensuring long-term consistency. However, exist…
FinVault: Benchmarking Financial Agent Safety in Execution-Grounded Environments
Zhi Yang, Runguo Li, Qiqi Qiang +15
Financial agents powered by large language models (LLMs) are increasingly deployed for investment analysis, risk assessment, and automated decision-making, where their abilities to…
Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning
Chengwen Liu, Xiaomin Yu, Zhuoyue Chang +15
In real-world video question answering scenarios, videos often provide only localized visual cues, while verifiable answers are distributed across the open web; models therefore ne…
DR-LoRA: Dynamic Rank LoRA for Fine-Tuning Mixture-of-Experts Models
Guanzhi Deng, Bo Li, Ronghao Chen +5
Mixture-of-Experts (MoE) has become a prominent paradigm for scaling Large Language Models (LLMs). Parameter-efficient fine-tuning methods, such as LoRA, are widely adopted to adap…
KnowMe-Bench: Benchmarking Person Understanding for Lifelong Digital Companions
Tingyu Wu, Zhisheng Chen, Ziyan Weng +8
Existing long-horizon memory benchmarks mostly use multi-turn dialogues or synthetic user histories, which makes retrieval performance an imperfect proxy for person understanding.…
Octopus: Agentic Multimodal Reasoning with Six-Capability Orchestration
Yifu Guo, Zishan Xu, Zhiyuan Yao +6
Existing multimodal reasoning models and frameworks suffer from fundamental architectural limitations: most lack the human-like ability to autonomously explore diverse reasoning pa…