arXiv AI
Jul 24
AI Assistants Overassist
arXiv:2607. 21306v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems.
AI Assistance Reduces Persistence and Hurts Independent Performance
arXiv:2604. 04721v3 Announce Type: replace Abstract: People often optimize for long-term goals in collaboration: A mentor or companion doesn't just answer questions, but also scaffolds learning, tracks progress, and prioritizes the other person's growth over immediate results.
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arXiv AI
Jun 2
Beyond Access: Guided LLM Scaffolding for Independent Learning in Undergraduate Statistics
arXiv:2606. 01375v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly entering students' learning practices, but their educational value depends on whether they support reasoning or enable task completion without engagement.
arXiv AI
2d ago
Demystifying Agent Skills: Why They Work-Until They Don't
arXiv:2608. 14036v1 Announce Type: new Abstract: Skills have emerged as a practical and effective approach for enhancing LLM agents at inference time through structured packages of knowledge.
arXiv AI
Jun 4
Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents
arXiv:2606. 04815v1 Announce Type: cross Abstract: Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments.
arXiv AI
Jul 7
Interactive Learning for LLM Reasoning
arXiv:2509. 26306v5 Announce Type: replace Abstract: Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large Language Models (LLMs), thereby constructing stronger multi-agent systems (MAS).
arXiv AI
Jun 8
How AI Agents Reshape Knowledge Work: Autonomy, Efficiency, and Scope
arXiv:2606. 07489v1 Announce Type: new Abstract: Frontier AI systems are bridging the gap between intelligence and utility by shifting from conversational assistants to autonomous agents that execute tasks end to end.
arXiv AI
Jul 14
Measuring AI Ability to Complete Long Software Tasks
arXiv:2503. 14499v4 Announce Type: replace Abstract: Despite rapid progress on AI benchmarks, the real-world meaning of benchmark performance remains unclear.
arXiv AI
Jun 2
Test-Time Deep Thinking to Explore Implicit Rules
arXiv:2605. 24828v2 Announce Type: replace Abstract: With the continuous advancement of Large Language Models (LLMs), intelligent agents are becoming increasingly vital.
arXiv AI
Aug 11
Search-G1: Grounded Search Agents via Representation-Based Intrinsic Rewards
arXiv:2608. 07531v1 Announce Type: cross Abstract: Search-augmented language agents should retrieve external information only when necessary and ground their answers in retrieved evidence.
arXiv AI
Jun 2
AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
arXiv:2606. 02461v1 Announce Type: new Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future episodes.
arXiv AI
Jun 3
AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
arXiv:2606. 02461v2 Announce Type: replace Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future episodes.
arXiv AI
Aug 10
Ask-E: An Environment for Calibrated Question Generation
arXiv:2608. 06933v1 Announce Type: cross Abstract: Today, we improve models by training and evaluating them on problems at the frontier of their abilities.