3 citations · 8 across the 31 of their papers we have counts for
15 papers · 1 filter
OR-License: Evaluating LLM Agents as Real-World Operations Research Practitioners
Peisong Wang, Feixue Liu, Yize Meng +16
Can large language model (LLM) agents deliver expert-level operations research (OR) solutions directly from original client materials, without prior expert reformulation? Existing…
TrajLong: Co-Designing Agentic and Long-Context Supervision for Mid-Training
Miao Peng, Qintong Zhang, Nuo Chen +8
LLM agents for coding, search, and workplace tasks increasingly rely on long-context capabilities to effectively aggregate and reason over extended interaction histories. Recent wo…
Scalable Frequency- and Length-Aware Subdocument Deduplication for Large Language Model Pretraining
Hai Wang, Chenhao Wang, Qifeng Cai +6
Large-scale pretraining corpora contain substantial duplicate content. Although document-level deduplication is widely used, removing subdocument-level redundancy remains challengi…
Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild
Mao Zheng, Zheng Li, Tao Chen +10
Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B, and 30B-A3B (MoE), all of wh…
WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
Zinan Zheng, Yang Liu, Nuo Chen +3
Accurate weather forecast reporting enables individuals and communities to better plan daily activities and agricultural operations. However, the current reporting process primaril…
LoopRPT: Reinforcement Pre-Training for Looped Language Models
Guo Tang, Shixin Jiang, Heng Chang +7
Looped language models (LoopLMs) perform iterative latent computation to refine internal representations, offering an alternative to explicit chain-of-thought (CoT) reasoning. Howe…
Incentivizing In-depth Reasoning over Long Contexts with Process Advantage Shaping
Miao Peng, Weizhou Shen, Nuo Chen +3
Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective in enhancing LLMs short-context reasoning, but its performance degrades in long-context scenarios that re…
NPG-Muse: Scaling Long Chain-of-Thought Reasoning with NP-Hard Graph Problems
Yuyao Wang, Bowen Liu, Jianheng Tang +6
Reasoning Large Language Models (RLLMs) have recently achieved remarkable progress on complex reasoning tasks, largely enabled by their long chain-of-thought (Long CoT) capabilitie…
How does Misinformation Affect Large Language Model Behaviors and Preferences?
Miao Peng, Nuo Chen, Jianheng Tang +1
Large Language Models (LLMs) have shown remarkable capabilities in knowledge-intensive tasks, while they remain vulnerable when encountering misinformation. Existing studies have e…
Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners
Miao Peng, Nuo Chen, Zongrui Suo +1
Despite significant advancements in Large Language Models (LLMs), developing advanced reasoning capabilities in LLMs remains a key challenge. Process Reward Models (PRMs) have demo…
GCoder: Improving Large Language Model for Generalized Graph Problem Solving
Qifan Zhang, Xiaobin Hong, Jianheng Tang +5
Large Language Models (LLMs) have demonstrated strong reasoning abilities, making them suitable for complex tasks such as graph computation. Traditional reasoning steps paradigm fo…
GraphWiz: An Instruction-Following Language Model for Graph Problems
Nuo Chen, Yuhan Li, Jianheng Tang +1
Large language models (LLMs) have achieved impressive success across several fields, but their proficiency in understanding and resolving complex graph problems is less explored. T…
Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term Conversations
Nuo Chen, Hongguang Li, Juhua Huang +2
Existing retrieval-based methods have made significant strides in maintaining long-term conversations. However, these approaches face challenges in memory database management and a…
Is Bigger and Deeper Always Better? Probing LLaMA Across Scales and Layers
Nuo Chen, Ning Wu, Shining Liang +4
This paper presents an in-depth analysis of Large Language Models (LLMs), focusing on LLaMA, a prominent open-source foundational model in natural language processing. Instead of a…
Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations
Nuo Chen, Zinan Zheng, Ning Wu +3
Existing research predominantly focuses on developing powerful language learning models (LLMs) for mathematical reasoning within monolingual languages, with few explorations in pre…