2 citations · 3 across the 12 of their papers we have counts for
13 papers
PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing
Donghao Zhou, Jia-Hui Pan, Fan Zhang +6
Robotic bin packing requires long-horizon sequential decision-making, as each object placement affects the available space for subsequent packing. Existing methods primarily rely o…
AgenticGen: Reward-Guided Agentic Video Generation for Advertising
Xingyuan Bu, Chengru Song, Hao Zhou +9
Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose success is measured by online business metrics. Recent video…
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Shilong Li, Xingyuan Bu, Wenjie Wang +22
AI agents with advanced reasoning and tool-use capabilities have demonstrated impressive performance in web browsing for deep search. However, existing benchmarks such as BrowseCom…
KORGym: A Dynamic Game Platform for LLM Reasoning Evaluation
Jiajun Shi, Jian Yang, Jiaheng Liu +26
Recent advancements in large language models (LLMs) underscore the need for more comprehensive evaluation methods to accurately assess their reasoning capabilities. Existing benchm…
DREAM: Disentangling Risks to Enhance Safety Alignment in Multimodal Large Language Models
Jianyu Liu, Hangyu Guo, Ranjie Duan +14
Multimodal Large Language Models (MLLMs) pose unique safety challenges due to their integration of visual and textual data, thereby introducing new dimensions of potential attacks…
Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?
Yancheng He, Shilong Li, Jiaheng Liu +8
Recently, o1-like models have drawn significant attention, where these models produce the long Chain-of-Thought (CoT) reasoning steps to improve the reasoning abilities of existing…
A Comprehensive Survey on Long Context Language Modeling
Jiaheng Liu, Dawei Zhu, Zhiqi Bai +34
Efficient processing of long contexts has been a persistent pursuit in Natural Language Processing. With the growing number of long documents, dialogues, and other textual data, it…
AIR: Complex Instruction Generation via Automatic Iterative Refinement
Wei Liu, Yancheng He, Hui Huang +5
With the development of large language models, their ability to follow simple instructions has significantly improved. However, adhering to complex instructions remains a major cha…
"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models
Jihao Gu, Yingyao Wang, Pi Bu +17
The evaluation of factual accuracy in large vision language models (LVLMs) has lagged behind their rapid development, making it challenging to fully reflect these models' knowledge…
MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training
Hui Huang, Jiaheng Liu, Yancheng He +5
Complex instruction-following with elaborate constraints is imperative for Large Language Models (LLMs). While existing methods have constructed data for complex instruction alignm…
Token Preference Optimization with Self-Calibrated Visual-Anchored Rewards for Hallucination Mitigation
Jihao Gu, Yingyao Wang, Meng Cao +5
Direct Preference Optimization (DPO) has been demonstrated to be highly effective in mitigating hallucinations in Large Vision Language Models (LVLMs) by aligning their outputs mor…
Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models
Yancheng He, Shilong Li, Jiaheng Liu +15
New LLM evaluation benchmarks are important to align with the rapid development of Large Language Models (LLMs). In this work, we present Chinese SimpleQA, the first comprehensive…
2D-DPO: Scaling Direct Preference Optimization with 2-Dimensional Supervision
Shilong Li, Yancheng He, Hui Huang +7
Recent advancements in Direct Preference Optimization (DPO) have significantly enhanced the alignment of Large Language Models (LLMs) with human preferences, owing to its simplicit…