collaborators

6 papers

cs.CL2026

SOMA-SQL: Resolving Multi-Source Ambiguity in NL-to-SQL via Synthetic Log and Execution Probing

Sai Ashish Somayajula, Marianne Menglin Liu, Chuan Lei +9

Natural language interfaces to databases aim to translate user questions into executable SQL, yet remain brittle in real-world settings where questions are underspecified and schem…

cs.CL2026

ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering

Marianne Menglin Liu, Daniel Garcia, Fjona Parllaku +3

Large language model (LLM) agents rely on external tools to solve complex tasks, but real-world toolsets often contain redundant tools with overlapping names and descriptions, intr…

cs.CL2026

Think Twice Before You Write -- an Entropy-based Decoding Strategy to Enhance LLM Reasoning

Jiashu He, Meizhu Liu, Olaitan P Olaleye +9

Decoding strategies play a central role in shaping the reasoning ability of large language models (LLMs). Traditional methods such as greedy decoding and beam search often suffer f…

cs.CL2026

LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding

Zhivar Sourati, Zheng Wang, Marianne Menglin Liu +8

Question answering over visually rich documents (VRDs) requires reasoning not only over isolated content but also over documents' structural organization and cross-page dependencie…

cs.SE2025

Routesplain: Towards Faithful and Intervenable Routing for Software-related Tasks

Adam Štorek, Adam Å torek, Vikas Upadhyay +7

LLMs now tackle a wide range of software-related tasks, yet we show that their performance varies markedly both across and within these tasks. Routing user queries to the appropria…

cs.CL2025

RAG Makes Guardrails Unsafe? Investigating Robustness of Guardrails under RAG-style Contexts

Yining She, Daniel W. Peterson, Marianne Menglin Liu +4

With the increasing adoption of large language models (LLMs), ensuring the safety of LLM systems has become a pressing concern. External LLM-based guardrail models have emerged as…