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cs.AI2026

LLM Capability Limits: Static Emergence and Dynamic Boundary Control

Yi Liu

Test-time emergence in LLM systems has a deployment boundary: additional computation can realize decisions already supported by the deployed information--execution structure, while…

cs.AI2026

BankerToolBench: Evaluating AI Agents in End-to-End Investment Banking Workflows

Elaine Lau, Markus Dücker, Ronak Chaudhary +24

Existing AI benchmarks lack the fidelity to assess economically meaningful progress on professional workflows. To evaluate frontier AI agents in a high-value, labor-intensive profe…

cs.AI2026

Answering the Unanswerable Is to Err Knowingly: Analyzing and Mitigating Abstention Failures in Large Reasoning Models

Yi Liu, Xiangyu Liu, Zequn Sun +1

Large reasoning models (LRMs) have shown remarkable progress on complex reasoning tasks. However, some questions posed to LRMs are inherently unanswerable, such as math problems la…

cs.AI2025

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning

Rongzhi Zhu, Yi Liu, Zequn Sun +2

Large reasoning models (LRMs) have significantly advanced performance on complex tasks, yet their tendency to overthink introduces inefficiencies. This study investigates the inter…

cs.AI2025

Controllable Protein Sequence Generation with LLM Preference Optimization

Xiangyu Liu, Yi Liu, Silei Chen +1

Designing proteins with specific attributes offers an important solution to address biomedical challenges. Pre-trained protein large language models (LLMs) have shown promising res…