22 citations · 23 across the 19 of their papers we have counts for
20 papers
Local Sparsity Enables Unsupervised LLM Safety Detection
Xin Chen, Gil Kur, Alexander Shevchenko +1
Deployment-time safety methods for large language models (LLMs) are predominantly supervised and assume access to unsafe training data. Nevertheless, new attacks and harm categorie…
xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems
Yongchang Peng, Qingshui Gu, Liya Zhu +31
Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally make in practice. Real-world…
Enhancing VLM Reward Models Through Structure-Aware Fine-Tuning
Pyrros Koussios, Chenhao Li, Xin Chen +1
Designing effective reward functions remains a major bottleneck in Reinforcement Learning (RL). Recent work uses large foundation Vision-Language Models (VLMs) as reward models, co…
GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training
Yuan Cao, Dezhi Ran, Mengzhou Wu +9
Post-training GUI agents in interactive environments is critical for developing generalization and long-horizon planning capabilities. However, training on real-world applications…
OpAgent: Operator Agent for Web Navigation
Yuyu Guo, Wenjie Yang, Siyuan Yang +12
To fulfill user instructions, autonomous web agents must contend with the inherent complexity and volatile nature of real-world websites. Conventional paradigms predominantly rely…
AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent
Yinyi Luo, Yiqiao Jin, Weichen Yu +6
While large language model (LLM) multi-agent systems achieve superior reasoning performance through iterative debate, practical deployment is limited by their high computational co…
LongCat-Flash-Thinking-2601 Technical Report
Meituan LongCat Team, Anchun Gui, Bei Li +162
We introduce LongCat-Flash-Thinking-2601, a 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model with superior agentic reasoning capability. LongCat-Flash-Thi…
Gaussian Process Bandit Optimization with Machine Learning Predictions and Application to Hypothesis Generation
Xin Jennifer Chen, Yunjin Tong
Many real-world optimization problems involve an expensive ground-truth oracle (e.g., human evaluation, physical experiments) and a cheap, low-fidelity prediction oracle (e.g., mac…
Dual-Phase LLM Reasoning: Self-Evolved Mathematical Frameworks
ShaoZhen Liu, Xinting Huang, Houwen Peng +4
In recent years, large language models (LLMs) have demonstrated significant potential in complex reasoning tasks like mathematical problem-solving. However, existing research predo…
EDCO: Dynamic Curriculum Orchestration for Domain-specific Large Language Model Fine-tuning
Jing-Cheng Pang, Liu Sun, Chang Zhou +10
Domain-specific large language models (LLMs), typically developed by fine-tuning a pre-trained general-purpose LLM on specialized datasets, represent a significant advancement in a…
Efficient Context Scaling with LongCat ZigZag Attention
Chen Zhang, Yang Bai, Jiahuan Li +19
We introduce LongCat ZigZag Attention (LoZA), which is a sparse attention scheme designed to transform any existing full-attention models into sparse versions with rather limited c…
Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers
Xin Chen, Feng Jiang, Yiqian Zhang +5
Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain fundamentally limited by a \emph{blind self…
LFS: Learnable Frame Selector for Event-Aware and Temporally Diverse Video Captioning
Lianying Chao, Linfeng Yin, Peiyu Ren +8
Video captioning models convert frames into visual tokens and generate descriptions with large language models (LLMs). Since encoding all frames is prohibitively expensive, uniform…
All-Quadrant Bounded Clipping GRPO: Closing the Unbounded Blind Spot for Stable and Generalizable Training
Chi Liu, Xin Chen
Group Relative Policy Optimization (GRPO) has emerged as a popular algorithm for reinforcement learning with large language models (LLMs). However, GRPO inherits PPO's token-level…
X-GridAgent: An LLM-Powered Agentic AI System for Assisting Power Grid Analysis
Yihan, Wen, Xin Chen
The growing complexity of power system operations has created an urgent need for intelligent, automated tools to support reliable and efficient grid management. Conventional analys…
Learning Safety Constraints for Large Language Models
Xin Chen, Yarden As, Andreas Krause
Large language models (LLMs) have emerged as powerful tools but pose significant safety risks through harmful outputs and vulnerability to adversarial attacks. We propose SaP, shor…
Gradient Co-occurrence Analysis for Detecting Unsafe Prompts in Large Language Models
Jingyuan Yang, Bowen Yan, Rongjun Li +4
Unsafe prompts pose significant safety risks to large language models (LLMs). Existing methods for detecting unsafe prompts rely on data-driven fine-tuning to train guardrail model…
AI-Driven Day-to-Day Route Choice
Leizhen Wang, Peibo Duan, Zhengbing He +5
Understanding travelers' route choices can help policymakers devise optimal operational and planning strategies for both normal and abnormal circumstances. However, existing choice…
Exploring and Addressing Reward Confusion in Offline Preference Learning
Xin Chen, Sam Toyer, Florian Shkurti
Spurious correlations in a reward model's training data can prevent Reinforcement Learning from Human Feedback (RLHF) from identifying the desired goal and induce unwanted behavior…
Diminishing Stereotype Bias in Image Generation Model using Reinforcemenlent Learning Feedback
Xin Chen, Virgile Foussereau
This study addresses gender bias in image generation models using Reinforcement Learning from Artificial Intelligence Feedback (RLAIF) with a novel Denoising Diffusion Policy Optim…