4 papers · 1 filter
Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails
Xin Liu, Simin Ma, Shujian Liu +5
Large language models (LLMs) achieve strong performance across many tasks, but their high computational cost limits deployment in resource-constrained environments. Knowledge Disti…
LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries
Ming Yin, Dinghan Shen, Silei Xu +11
Tool calling has emerged as a critical capability for AI agents. In contrast to conventional tool calling frameworks that rely on static, provider-specific tool definitions, the Mo…
Aligning Multilingual Reasoning with Verifiable Semantics from a High-Resource Expert Model
Fahim Faisal, Kaiqiang Song, Song Wang +4
While reinforcement learning has advanced the reasoning abilities of Large Language Models (LLMs), these gains are largely confined to English, creating a significant performance d…
Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL
Qingyun Zeng, Simin Ma, Arash Niknafs +2
The rise of Large Language Models (LLMs) has significantly advanced Text-to-SQL (NL2SQL) systems, yet evaluating the semantic equivalence of generated SQL remains a challenge, espe…