collaborators

10 papers

cs.AI2026

SCP-NL2TL: Selective Conformal Prediction with Semantic Verification for Natural Language to Temporal Logic Specifications

Yixuan Wang, Licheng Luo, Yu Fu +3

Translating natural language instructions into machine-interpretable formal specifications enables robots and autonomous systems to plan, reason, and formally verify their behavior…

cs.IR2026

SCOReD: Student-Aware CoT Optimization for Recommendation Distillation

Haz Sameen Shahgir, Yufei Li, Xiaohan Wei +8

Chain-of-thought (CoT) distillation in the recommendation domain is a necessary precursor to RL training, but raw teacher traces are ill-suited to this task. Large teachers approac…

cs.LG2026

Multi-modal Rail Crossing Safety Analysis

Paimon Goulart, Chansong Lim, Nícolas Roque dos Santos +4

Given one or more images of a railway crossing, can we leverage visual cues that allow us to robustly estimate how safe it is? Can we improve our ability to do so by introducing st…

cs.CR2026

D-Judge: Disrupting Multi-Turn Jailbreaks using Semantics-Preserving Output Rewriting

Huanli Gong, Zhipeng Wei, Yu Fu +4

Multi-turn jailbreak attacks pose a growing threat to large language model (LLM) safety because they exploit feedback from auxiliary judge models to iteratively refine prompts towa…

cs.CL2026

Do Reasoning LLMs Refuse What They Infer in Long Contexts?

Yu Fu, Haz Sameen Shahgir, Huanli Gong +3

Long-context LLMs can infer objectives that are not stated explicitly. This capability is useful for reasoning over documents, code, retrieved evidence, and tool traces, but it als…

cs.CV2026

VLMs Need Words: Vision Language Models Ignore Visual Detail In Favor of Semantic Anchors

Haz Sameen Shahgir, Xiaofu Chen, Yu Fu +4

Vision-language models (VLMs) have achieved impressive performance across a wide range of multimodal tasks. However, they often fail on tasks that require fine-grained visual perce…