collaborators

7 papers

cs.CL2026

SkillForge: Compositional Skill Synthesis with Verification-in-the-Loop for Generating Formally Verified Dafny Programs

Yanming Liu, Xinyue Peng, Jiannan Cao +2

Generating formally verified programs from natural language remains challenging: existing approaches either produce code in a single pass without recourse when verification fails,…

cs.RO2026

SRL-MPC: Shape-Aware Reinforcement Learned Model Predictive Control

Ruihua Han, Rui Gao, Zhe Liu +6

Safe and efficient shape-aware navigation in heterogeneous crowds and robot fleets remains challenging. Traditional approaches often assume homogeneous robots, sparse workspaces, s…

cs.CL2026

Hubs or Fringes: Pretraining Data Selection via Web Graph Centrality

Vedant Badoni, Danqi Chen, Xinyi Wang

The performance of modern language models depends critically on pretraining data composition. Yet existing data selection methods rely on auxiliary classifiers for document scoring…

cs.RO2026

IR-SIM: A Lightweight Declarative Simulator for Navigation Learning and Benchmarking

Ruihua Han, Shuai Wang, Chengyang Li +8

Developing navigation policies requires simulation scenarios that support repeatable training and evaluation. Despite the availability of numerous simulators, constructing diverse…

cs.CL2026

Dep-Search: Learning Dependency-Aware Reasoning Traces with Persistent Memory

Yanming Liu, Xinyue Peng, Zixuan Yan +7

Large Language Models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks, particularly when augmented with search mechanisms that enable systematic explora…

cs.CL2026

NC2C: Automated Convexification of Generic Non-Convex Optimization Problems

Xinyue Peng, Yanming Liu, Yihan Cang +4

Non-convex optimization problems are pervasive across mathematical programming, engineering design, and scientific computing, often posing intractable challenges for traditional so…

cs.CL2026

ToolGate: Contract-Grounded and Verified Tool Execution for LLMs

Yanming Liu, Xinyue Peng, Jiannan Cao +5

Large Language Models (LLMs) augmented with external tools have demonstrated remarkable capabilities in complex reasoning tasks. However, existing frameworks rely heavily on natura…