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TeamLLM: A Human-Like Team-Oriented Collaboration Framework for Multi-Step Contextualized Tasks
Xiangyu Wang, Jin Wu, Haoran Shi +3
Recently, multi-Large Language Model (LLM) frameworks have been proposed to solve contextualized tasks. However, these frameworks do not explicitly emulate human team role division…
Asymmetric Actor-Critic for Multi-turn LLM Agents
Shuli Jiang, Zhaoyang Zhang, Yi Zhang +3
Large language models (LLMs) exhibit strong reasoning and conversational abilities, but ensuring reliable behavior in multi-turn interactions remains challenging. In many real-worl…
Ideology as a Problem: Lightweight Logit Steering for Annotator-Specific Alignment in Social Media Analysis
Wei Xia, Haowen Tang, Luozheng Li
LLMs internally organize political ideology along low-dimensional structures that are partially, but not fully aligned with human ideological space. This misalignment is systematic…
SDA: Steering-Driven Distribution Alignment for Open LLMs without Fine-Tuning
Wei Xia, Zhi-Hong Deng
With the rapid advancement of large language models (LLMs), their deployment in real-world applications has become increasingly widespread. LLMs are expected to deliver robust perf…
Learning to Focus: Focal Attention for Selective and Scalable Transformers
Dhananjay Ram, Wei Xia, Stefano Soatto
Attention is a core component of transformer architecture, whether encoder-only, decoder-only, or encoder-decoder model. However, the standard softmax attention often produces nois…
Maximally-Informative Retrieval for State Space Model Generation
Evan Becker, Benjamin Bowman, Matthew Trager +4
Given a query and dataset, the optimal way of answering the query is to make use all the information available. Modern LLMs exhibit impressive ability to memorize training data, bu…