Chris Ngo

According to our database1, Chris Ngo authored at least 17 papers between 2024 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Polyglot-Lion: Efficient Multilingual ASR for Singapore via Balanced Fine-Tuning of Qwen3-ASR.
CoRR, March, 2026

Selective Steering: Norm-Preserving Control Through Discriminative Layer Selection.
CoRR, January, 2026

RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models.
CoRR, January, 2026

2025
S-Chain: Structured Visual Chain-of-Thought For Medicine.
CoRR, October, 2025

A Novel Framework for Automated Explain Vision Model Using Vision-Language Models.
CoRR, August, 2025

Multimodal Chain of Continuous Thought for Latent-Space Reasoning in Vision-Language Models.
CoRR, August, 2025

Audio-3DVG: Unified Audio - Point Cloud Fusion for 3D Visual Grounding.
CoRR, July, 2025

Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles.
CoRR, June, 2025

RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints.
CoRR, June, 2025

IQBench: How "Smart" Are Vision-Language Models? A Study with Human IQ Tests.
CoRR, May, 2025

RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search.
CoRR, April, 2025

MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation.
CoRR, April, 2025

Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't.
CoRR, March, 2025

SilVar: Speech-Driven Multimodal Model for Reasoning Visual Question Answering and Object Localization.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024
MoD: A Distribution-Based Approach for Merging Large Language Models.
CoRR, 2024


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