1 citations · 2 across the 11 of their papers we have counts for
11 papers
InCoder-32B-Thinking: Industrial Code World Model for Thinking
Jian Yang, Wei Zhang, Jiajun Wu +22
Industrial software development across chip design, GPU optimization, and embedded systems lacks expert reasoning traces showing how engineers reason about hardware constraints and…
Large-Scale Terminal Agentic Trajectory Generation from Dockerized Environments
Siwei Wu, Yizhi Li, Yuyang Song +8
Training agentic models for terminal-based tasks critically depends on high-quality terminal trajectories that capture realistic long-horizon interactions across diverse domains. H…
Close the Loop: Synthesizing Infinite Tool-Use Data via Multi-Agent Role-Playing
Yuwen Li, Wei Zhang, Zelong Huang +8
Enabling Large Language Models (LLMs) to reliably invoke external tools remains a critical bottleneck for autonomous agents. Existing approaches suffer from three fundamental chall…
AGRO-SQL: Agentic Group-Relative Optimization with High-Fidelity Data Synthesis
Cehua Yang, Dongyu Xiao, Junming Lin +7
The advancement of Text-to-SQL systems is currently hindered by the scarcity of high-quality training data and the limited reasoning capabilities of models in complex scenarios. In…
Using GUI Agent for Electronic Design Automation
Chunyi Li, Longfei Li, Zicheng Zhang +4
Graphical User Interface (GUI) agents adopt an end-to-end paradigm that maps a screenshot to an action sequence, thereby automating repetitive tasks in virtual environments. Howeve…
From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence
Jian Yang, Xianglong Liu, Weifeng Lv +68
Large language models (LLMs) have fundamentally transformed automated software development by enabling direct translation of natural language descriptions into functional code, dri…
SIEVE: Selective Integrity Verification and Escalation for Defending LLM Agents against Indirect Prompt Injection
Zhibo Liang, Tianze Hu, Zaiye Chen +1
Large Language Models (LLMs) are increasingly used as the core of agentic systems due to their strong reasoning, planning, and tool-use capabilities. By interacting with external e…
Generating Feasible and Diverse Synthetic Populations Using Diffusion Models
Min Tang, Peng Lu, Qing Feng
Population synthesis is a critical task that involves generating synthetic yet realistic representations of populations. It is a fundamental problem in agent-based modeling (ABM),…
Temporal-IRL: Modeling Port Congestion and Berth Scheduling with Inverse Reinforcement Learning
Guo Li, Zixiang Xu, Wei Zhang +5
Predicting port congestion is crucial for maintaining reliable global supply chains. Accurate forecasts enableimprovedshipment planning, reducedelaysand costs, and optimizeinventor…
Concise Reasoning via Reinforcement Learning
Mehdi Fatemi, Banafsheh Rafiee, Mingjie Tang +1
A major drawback of reasoning models is their excessive token usage, inflating computational cost, resource demand, and latency. We show this verbosity stems not from deeper reason…
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
Yizhe Huang, Xingbo Wang, Hao Liu +7
Traditional interactive environments limit agents' intelligence growth with fixed tasks. Recently, single-agent environments address this by generating new tasks based on agent act…