FinToolBench: Evaluating LLM Agents for Real-World Financial Tool Use Paper • 2603.08262 • Published 11 days ago • 33
In-Context Reinforcement Learning for Tool Use in Large Language Models Paper • 2603.08068 • Published 11 days ago • 39
Less is Enough: Synthesizing Diverse Data in Feature Space of LLMs Paper • 2602.10388 • Published Feb 11 • 243
Believe Your Model: Distribution-Guided Confidence Calibration Paper • 2603.03872 • Published 16 days ago • 39
Next Embedding Prediction Makes World Models Stronger Paper • 2603.02765 • Published 17 days ago • 20
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity Paper • 2506.06941 • Published Jun 7, 2025 • 16
PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning Paper • 2601.05593 • Published Jan 9 • 86
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration Paper • 2602.05400 • Published Feb 5 • 349
Weak-Driven Learning: How Weak Agents make Strong Agents Stronger Paper • 2602.08222 • Published Feb 9 • 283
ASTRA: Automated Synthesis of agentic Trajectories and Reinforcement Arenas Paper • 2601.21558 • Published Jan 29 • 60
Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text Paper • 2601.22975 • Published Jan 30 • 109
Scaling Embeddings Outperforms Scaling Experts in Language Models Paper • 2601.21204 • Published Jan 29 • 102
AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security Paper • 2601.18491 • Published Jan 26 • 125
Can LLMs Clean Up Your Mess? A Survey of Application-Ready Data Preparation with LLMs Paper • 2601.17058 • Published Jan 22 • 190