Collaborate, Deliberate, Evaluate: How LLM Alignment Affects Coordinated Multi-Agent Outcomes
Fuente:
arXiv
Saved in:
| Main Authors: | Nath, Abhijnan, Graff, Carine, Krishnaswamy, Nikhil |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CRAFT: Grounded Multi-Agent Coordination Under Partial Information
by: Nath, Abhijnan, et al.
Published: (2026)
by: Nath, Abhijnan, et al.
Published: (2026)
Frictional Agent Alignment Framework: Slow Down and Don't Break Things
by: Nath, Abhijnan, et al.
Published: (2025)
by: Nath, Abhijnan, et al.
Published: (2025)
Learning "Partner-Aware" Collaborators in Multi-Party Collaboration
by: Nath, Abhijnan, et al.
Published: (2025)
by: Nath, Abhijnan, et al.
Published: (2025)
Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignment
by: Pustejovsky, James, et al.
Published: (2026)
by: Pustejovsky, James, et al.
Published: (2026)
Simultaneous Reward Distillation and Preference Learning: Get You a Language Model Who Can Do Both
by: Nath, Abhijnan, et al.
Published: (2024)
by: Nath, Abhijnan, et al.
Published: (2024)
CascadeDebate: Multi-Agent Deliberation for Cost-Aware LLM Cascades
by: Chang, Raeyoung, et al.
Published: (2026)
by: Chang, Raeyoung, et al.
Published: (2026)
Contextual Drag: How Errors in the Context Affect LLM Reasoning
by: Cheng, Yun, et al.
Published: (2026)
by: Cheng, Yun, et al.
Published: (2026)
On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025)
by: Liu, Yixin, et al.
Published: (2025)
AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents
by: Ma, Chang, et al.
Published: (2024)
by: Ma, Chang, et al.
Published: (2024)
Any Other Thoughts, Hedgehog? Linking Deliberation Chains in Collaborative Dialogues
by: Nath, Abhijnan, et al.
Published: (2024)
by: Nath, Abhijnan, et al.
Published: (2024)
Revisiting the Superficial Alignment Hypothesis
by: Raghavendra, Mohit, et al.
Published: (2024)
by: Raghavendra, Mohit, et al.
Published: (2024)
Multi-LLM Collaboration for Medication Recommendation
by: Sanchez, Huascar, et al.
Published: (2025)
by: Sanchez, Huascar, et al.
Published: (2025)
Latent Collaboration in Multi-Agent Systems
by: Zou, Jiaru, et al.
Published: (2025)
by: Zou, Jiaru, et al.
Published: (2025)
Two Minds Better Than One: Collaborative Reward Modeling for LLM Alignment
by: Zhang, Jiazheng, et al.
Published: (2025)
by: Zhang, Jiazheng, et al.
Published: (2025)
LLM Probability Concentration: How Alignment Shrinks the Generative Horizon
by: Yang, Chenghao, et al.
Published: (2025)
by: Yang, Chenghao, et al.
Published: (2025)
Planning with Multi-Constraints via Collaborative Language Agents
by: Zhang, Cong, et al.
Published: (2024)
by: Zhang, Cong, et al.
Published: (2024)
Survey on Evaluation of LLM-based Agents
by: Yehudai, Asaf, et al.
Published: (2025)
by: Yehudai, Asaf, et al.
Published: (2025)
TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration
by: Du, Yuwei, et al.
Published: (2024)
by: Du, Yuwei, et al.
Published: (2024)
DeepCritic: Deliberate Critique with Large Language Models
by: Yang, Wenkai, et al.
Published: (2025)
by: Yang, Wenkai, et al.
Published: (2025)
Deliberation in Latent Space via Differentiable Cache Augmentation
by: Liu, Luyang, et al.
Published: (2024)
by: Liu, Luyang, et al.
Published: (2024)
Towards Efficient LLM Grounding for Embodied Multi-Agent Collaboration
by: Zhang, Yang, et al.
Published: (2024)
by: Zhang, Yang, et al.
Published: (2024)
FutureSim: Replaying World Events to Evaluate Adaptive Agents
by: Goel, Shashwat, et al.
Published: (2026)
by: Goel, Shashwat, et al.
Published: (2026)
Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control
by: Rezazadeh, Alireza, et al.
Published: (2025)
by: Rezazadeh, Alireza, et al.
Published: (2025)
How Does Response Length Affect Long-Form Factuality
by: Zhao, James Xu, et al.
Published: (2025)
by: Zhao, James Xu, et al.
Published: (2025)
How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs
by: Feng, Guhao, et al.
Published: (2024)
by: Feng, Guhao, et al.
Published: (2024)
CAMPHOR: Collaborative Agents for Multi-input Planning and High-Order Reasoning On Device
by: Fu, Yicheng, et al.
Published: (2024)
by: Fu, Yicheng, et al.
Published: (2024)
Reinforce LLM Reasoning through Multi-Agent Reflection
by: Yuan, Yurun, et al.
Published: (2025)
by: Yuan, Yurun, et al.
Published: (2025)
Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models
by: Nath, Vaskar, et al.
Published: (2025)
by: Nath, Vaskar, et al.
Published: (2025)
Evaluating Very Long-Term Conversational Memory of LLM Agents
by: Maharana, Adyasha, et al.
Published: (2024)
by: Maharana, Adyasha, et al.
Published: (2024)
A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning
by: Ji, Yixin, et al.
Published: (2025)
by: Ji, Yixin, et al.
Published: (2025)
Collaboratively adding new knowledge to an LLM
by: Lee, Rhui Dih, et al.
Published: (2024)
by: Lee, Rhui Dih, et al.
Published: (2024)
IntellAgent: A Multi-Agent Framework for Evaluating Conversational AI Systems
by: Levi, Elad, et al.
Published: (2025)
by: Levi, Elad, et al.
Published: (2025)
MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent
by: Yu, Hongli, et al.
Published: (2025)
by: Yu, Hongli, et al.
Published: (2025)
Position: The Most Expensive Part of an LLM should be its Training Data
by: Kandpal, Nikhil, et al.
Published: (2025)
by: Kandpal, Nikhil, et al.
Published: (2025)
Learning to Negotiate: Multi-Agent Deliberation for Collective Value Alignment in LLMs
by: Anantaprayoon, Panatchakorn, et al.
Published: (2026)
by: Anantaprayoon, Panatchakorn, et al.
Published: (2026)
Be My Eyes: Extending Large Language Models to New Modalities Through Multi-Agent Collaboration
by: Huang, James Y., et al.
Published: (2025)
by: Huang, James Y., et al.
Published: (2025)
CDQuant: Greedy Coordinate Descent for Accurate LLM Quantization
by: Nair, Pranav Ajit, et al.
Published: (2024)
by: Nair, Pranav Ajit, et al.
Published: (2024)
TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents
by: Djuhera, Aladin, et al.
Published: (2026)
by: Djuhera, Aladin, et al.
Published: (2026)
RLTHF: Targeted Human Feedback for LLM Alignment
by: Xu, Yifei, et al.
Published: (2025)
by: Xu, Yifei, et al.
Published: (2025)
A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement
by: Tang, Shengji, et al.
Published: (2025)
by: Tang, Shengji, et al.
Published: (2025)
Similar Items
-
CRAFT: Grounded Multi-Agent Coordination Under Partial Information
by: Nath, Abhijnan, et al.
Published: (2026) -
Frictional Agent Alignment Framework: Slow Down and Don't Break Things
by: Nath, Abhijnan, et al.
Published: (2025) -
Learning "Partner-Aware" Collaborators in Multi-Party Collaboration
by: Nath, Abhijnan, et al.
Published: (2025) -
Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignment
by: Pustejovsky, James, et al.
Published: (2026) -
Simultaneous Reward Distillation and Preference Learning: Get You a Language Model Who Can Do Both
by: Nath, Abhijnan, et al.
Published: (2024)