10 papers
Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Model
Nanbeige Lab, :, Chen Yang +23
We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-agent, and complex tool-use ta…
Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
Cheng-Han Huang, Yongliang Sun, Chaoyan Huang +2
Many combinatorial optimization problems admit quadratic unconstrained binary formulations (QUBO) which can often be relaxed to the box and optimized using scalable gradi…
Mutation-Guided Differentiable Quadratic Combinatorial Optimization
Yongliang Sun, Ismail Alkhouri, Cheng-Han Huang +3
Recent studies suggest that gradient-based methods applied to relaxed box-constrained Quadratic Unconstrained Binary Optimization (QUBO) formulations can outperform classical heuri…
DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents
Junshuo Zhang, Chengrui Huang, Feng Guo +6
Large language model (LLM) agents that follow the sequential "reason-then-act" paradigm have achieved superior performance in many complex tasks.However, these methods suffer from…
HTAA: Enhancing LLM Planning via Hybrid Toolset Agentization & Adaptation
Chengrui Huang, Junshuo Zhang, Zhiyuan Ma +7
Enabling large language models to scale and reliably use hundreds of tools is critical for real-world applications, yet challenging due to the inefficiency and error accumulation i…
KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning
Cheng Gao, Cheng Huang, Kangyang Luo +5
Enabling large language models (LLMs) to appropriately abstain from answering questions beyond their knowledge is crucial for mitigating hallucinations. While existing reinforcemen…