6 papers
Argus: A General-Purpose Agentic Reasoning Runtime for Long-Horizon Tasks
Boxiu Li, Zimo Wen, Yijia Fan +24
Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failure, hidden constraints, or a…
TPS-Bench: Evaluating AI Agents' Tool Planning \& Scheduling Abilities in Compounding Tasks
Hanwen Xu, Xuyao Huang, Yuzhe Liu +2
Large language model (LLM) agents have exhibited strong problem-solving competence across domains like research and coding. Yet, it remains underexplored whether LLM agents can tac…
Done Is Better than Perfect: Unlocking Efficient Reasoning by Structured Multi-Turn Decomposition
Zihao Zeng, Xuyao Huang, Boxiu Li +2
Large Reasoning Models (LRMs) are criticized for the excessively lengthy Chain-of-Thought (CoT) to derive the final answer, suffering from high first-token and overall latency. Typ…
Which Data Attributes Stimulate Math and Code Reasoning? An Investigation via Influence Functions
Siqi Kou, Qingyuan Tian, Hanwen Xu +2
Large language models (LLMs) have demonstrated remarkable reasoning capabilities in math and coding, often bolstered by post-training on the chain-of-thoughts (CoTs) generated by s…
RealSafe-R1: Safety-Aligned DeepSeek-R1 without Compromising Reasoning Capability
Yichi Zhang, Zihao Zeng, Dongbai Li +3
Large Reasoning Models (LRMs), such as OpenAI o1 and DeepSeek-R1, have been rapidly progressing and achieving breakthrough performance on complex reasoning tasks such as mathematic…
SIFT: Grounding LLM Reasoning in Contexts via Stickers
Zihao Zeng, Xuyao Huang, Boxiu Li +1
This paper identifies the misinterpretation of the context can be a significant issue during the reasoning process of large language models, spanning from smaller models like Llama…