5 papers
PRAXIS: Graph-Grounded Tacit Knowledge for Domain Code Generation
Xue Jiang, Tianyu Zhang, Lingwei Wu +7
LLM agents have achieved strong performance on general software engineering tasks, yet struggle with domain-specific code generation. We identify the root cause as the agent's lack…
Think Anywhere in Code Generation
Xue Jiang, Tianyu Zhang, Ge Li +8
Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer. However, this approach suffers from…
Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization
Jinghan Li, Junfeng Fang, Jinda Lu +5
Reinforcement Learning with Verifiable Rewards (RLVR) and Group Relative Policy Optimization (GRPO) have significantly advanced the reasoning capabilities of large language models.…
Shared Nature, Unique Nurture: PRISM for Pluralistic Reasoning via In-context Structure Modeling
Guancheng Tu, Shiyang Zhang, Tianyu Zhang +2
Large Language Models (LLMs) are converging towards a singular Artificial Hivemind, where shared Nature (pre-training priors) result in a profound collapse of distributional divers…
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin +1
Concept Bottleneck Models (CBMs) propose to enhance the trustworthiness of AI systems by constraining their decisions on a set of human-understandable concepts. However, CBMs typic…