5 papers
A Predictive-Prescriptive Analytics Framework for Fair Computed Tomography Scheduling and Radiologist Workload Allocation
Ludovico Ambrosi, Chandra Bortolotto, Sara Cambiaghi +3
Scheduling follow-up Computed Tomography (CT) examinations requires balancing two competing objectives: assigning patients as close as possible to their recommended examination dat…
Breaking Contextual Inertia: Reinforcement Learning with Single-Turn Anchors for Stable Multi-Turn Interaction
Xingwu Chen, Zhanqiu Zhang, Yiwen Guo +1
While LLMs demonstrate strong reasoning capabilities when provided with full information in a single turn, they exhibit substantial vulnerability in multi-turn interactions. Specif…
Reshaping Reasoning in LLMs: A Theoretical Analysis of RL Training Dynamics through Pattern Selection
Xingwu Chen, Tianle Li, Difan Zou
While reinforcement learning (RL) demonstrated remarkable success in enhancing the reasoning capabilities of language models, the training dynamics of RL in LLMs remain unclear. In…
Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression
Xingwu Chen, Miao Lu, Beining Wu +1
Using more test-time computation during language model inference, such as generating more intermediate thoughts or sampling multiple candidate answers, has proven effective in sign…
On the Robustness of Transformers against Context Hijacking for Linear Classification
Tianle Li, Chenyang Zhang, Xingwu Chen +2
Transformer-based Large Language Models (LLMs) have demonstrated powerful in-context learning capabilities. However, their predictions can be disrupted by factually correct context…