5 papers
COMAP: Co-Evolving World Models and Agent Policies for LLM Agents
Youwei Liu, Jian Wang, Hanlin Wang +1
Equipping language agents with world models enables them to anticipate environment dynamics and evaluate candidate actions before execution. However, existing textual world models…
ToolSpec: Accelerating Tool Calling via Schema-Aware and Retrieval-Augmented Speculative Decoding
Heming Xia, Yongqi Li, Cunxiao Du +2
Tool calling has greatly expanded the practical utility of large language models (LLMs) by enabling them to interact with external applications. As LLM capabilities advance, effect…
AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts
Keyu Li, Junhao Shi, Yang Xiao +11
Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. However, existing benchmarks remain f…
Foresight Optimization for Strategic Reasoning in Large Language Models
Jiashuo Wang, Jiawen Duan, Jian Wang +6
Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-based LLMs to perform effectiv…
daVinci-Agency: Unlocking Long-Horizon Agency Data-Efficiently
Mohan Jiang, Dayuan Fu, Junhao Shi +8
While Large Language Models (LLMs) excel at short-term tasks, scaling them to long-horizon agentic workflows remains challenging. The core bottleneck lies in the scarcity of traini…