:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Amin-Naseri, Moin, Kim, Hannah, Hruschka, Estevam
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Machine Learning
Online Access:	https://arxiv.org/abs/2603.06915
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs
by: Pezeshkpour, Pouya, et al.
Published: (2026)

From Task Solving to Robust Real-World Adaptation in LLM Agents
by: Pezeshkpour, Pouya, et al.
Published: (2026)

Learning Beyond the Surface: How Far Can Continual Pre-Training with LoRA Enhance LLMs' Domain-Specific Insight Learning?
by: Pezeshkpour, Pouya, et al.
Published: (2025)

Insight-RAG: Enhancing LLMs with Insight-Driven Augmentation
by: Pezeshkpour, Pouya, et al.
Published: (2025)

Multi-Conditional Ranking with Large Language Models
by: Pezeshkpour, Pouya, et al.
Published: (2024)

Learning from Supervision with Semantic and Episodic Memory: A Reflective Approach to Agent Adaptation
by: Hassell, Jackson, et al.
Published: (2025)

Verification-Aware Planning for Multi-Agent Systems
by: Xu, Tianyang, et al.
Published: (2025)

FactLens: Benchmarking Fine-Grained Fact Verification
by: Mitra, Kushan, et al.
Published: (2024)

Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions
by: Pezeshkpour, Pouya, et al.
Published: (2024)

Align then Train: Efficient Retrieval Adapter Learning
by: Maekawa, Seiji, et al.
Published: (2026)

RECAP: REwriting Conversations for Intent Understanding in Agentic Planning
by: Mitra, Kushan, et al.
Published: (2025)

Do Agents Need to Plan Step-by-Step? Rethinking Planning Horizon in Data-Centric Tool Calling
by: Otani, Naoki, et al.
Published: (2026)

Mixed Signals: Decoding VLMs' Reasoning and Underlying Bias in Vision-Language Conflict
by: Pezeshkpour, Pouya, et al.
Published: (2025)

Natural Language Processing for Human Resources: A Survey
by: Otani, Naoki, et al.
Published: (2024)

Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks
by: Mishra, Aditi, et al.
Published: (2023)

Contrastive Perplexity for Controlled Generation: An Application in Detoxifying Large Language Models
by: Klein, Tassilo, et al.
Published: (2024)

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models
by: Bayat, Farima Fatahi, et al.
Published: (2025)

Evaluating Bias in LLMs for Job-Resume Matching: Gender, Race, and Education
by: Iso, Hayate, et al.
Published: (2025)

AgentEvolver: Towards Efficient Self-Evolving Agent System
by: Zhai, Yunpeng, et al.
Published: (2025)

Towards Probabilistic Question Answering Over Tabular Data
by: Shen, Chen, et al.
Published: (2025)

Towards Reliable Benchmarking: A Contamination Free, Controllable Evaluation Framework for Multi-step LLM Function Calling
by: Maekawa, Seiji, et al.
Published: (2025)

MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents
by: Zhang, Haozhen, et al.
Published: (2026)

AgenticGEO: A Self-Evolving Agentic System for Generative Engine Optimization
by: Yuan, Jiaqi, et al.
Published: (2026)

Thinking into the Future: Latent Lookahead Training for Transformers
by: Noci, Lorenzo, et al.
Published: (2026)

SELAUR: Self Evolving LLM Agent via Uncertainty-aware Rewards
by: Zhang, Dengjia, et al.
Published: (2026)

Symbolic Learning Enables Self-Evolving Agents
by: Zhou, Wangchunshu, et al.
Published: (2024)

Evolving LLMs' Self-Refinement Capability via Synergistic Training-Inference Optimization
by: Zeng, Yongcheng, et al.
Published: (2025)

How to Steer Your Multi-Agent System: Human-LLM Collaborative Planning
by: He, Zeyu, et al.
Published: (2026)

TTCS: Test-Time Curriculum Synthesis for Self-Evolving
by: Yang, Chengyi, et al.
Published: (2026)

Self-Evolving Critique Abilities in Large Language Models
by: Tang, Zhengyang, et al.
Published: (2025)

Guided Self-Evolving LLMs with Minimal Human Supervision
by: Yu, Wenhao, et al.
Published: (2025)

Less is More for Long Document Summary Evaluation by LLMs
by: Wu, Yunshu, et al.
Published: (2023)

Multilingual Self-Taught Faithfulness Evaluators
by: Alfano, Carlo, et al.
Published: (2025)

Universe Routing: Why Self-Evolving Agents Need Epistemic Control
by: Wang, Zhaohui Geoffrey
Published: (2026)

R-Zero: Self-Evolving Reasoning LLM from Zero Data
by: Huang, Chengsong, et al.
Published: (2025)

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
by: Zhang, Qizheng, et al.
Published: (2025)

Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI
by: Kandogan, Eser, et al.
Published: (2025)

MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining
by: Portes, Jacob, et al.
Published: (2023)

TodoEvolve: Learning to Architect Agent Planning Systems
by: Liu, Jiaxi, et al.
Published: (2026)

Diving into Self-Evolving Training for Multimodal Reasoning
by: Liu, Wei, et al.
Published: (2024)