From the 1 of 20 linked papers with an AI index.
20 papers
Rethinking the Evaluation of Harness Evolution for Agents
Yike Wang, Huaisheng Zhu, Zhengyu Hu +7
The paper reexamines how automatic harness evolution for large language model agents is evaluated, comparing it to simple test‑time scaling baselines and finding that it offers lim…
The Single-Multi Evolution Loop for Self-Improving Model Collaboration Systems
Shangbin Feng, Kishan Panaganti, Yulia Tsvetkov +1
Model collaboration -- systems where multiple language models (LMs) collaborate -- combines the strengths of diverse models with cost in loading multiple LMs. We improve efficiency…
MentorCollab: Large-to-Small Inference-Time Mentorship for Concise Reasoning in Language Models
Haojin Wang, Yike Wang, Shangbin Feng +2
Large reasoning models (LRMs) have demonstrated impressive reasoning capabilities, but their solutions are often verbose and computationally expensive, and taxing for users to read…
Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems
Ziyuan Yang, Wenxuan Ding, Shangbin Feng +1
Language models (LMs) are increasingly used in collaboration: multiple LMs trained by different parties collaborate through routing systems, multi-agent debate, model merging, and…
SPARTA ALIGNMENT: Collectively Aligning Multiple Language Models through Combat
Yuru Jiang, Wenxuan Ding, Shangbin Feng +2
We propose SPARTA ALIGNMENT, an algorithm to collectively align multiple LLMs through competition and combat. To complement a single model's lack of diversity in generation and bia…
Heterogeneous Swarms: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems
Shangbin Feng, Zifeng Wang, Palash Goyal +8
We propose Heterogeneous Swarms, an algorithm to design multi-LLM systems by jointly optimizing model roles and weights. We represent multi-LLM systems as directed acyclic graphs (…