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Ken Deng

6 accepted papers

2026

GeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation

CVPR 2026

We introduce GeoSAM2, a prompt-controllable framework for 3D part segmentation that casts the task as multi-view 2D mask prediction. Given a textureless object, we render normal and point maps from predefined viewpoints and accept simple 2D prompts--clicks or boxes--to guide part selection. These pr

Cited by 0SourceScholar
2026

SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models

ICML 2026poster

Evaluating large language models (LLMs) for software engineering has been limited by narrow task coverage, language bias, and insufficient alignment with real-world developer workflows. Existing benchmarks often focus on algorithmic problems or Python-centric bug fixing, leaving critical dimensions …

Cited by 0SourceScholar
2025

M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation

ACL 2025long

Repository-level code completion has drawn great attention in software engineering, and several benchmarks have been introduced. However, existing repository-level code completion benchmarks usually focus on a limited number of languages (<5), which cannot evaluate the general code intelligence abil…

2025

MTU-Bench: A Multi-granularity Tool-Use Benchmark for Large Language Models

ICLR 2025poster

Large Language Models (LLMs) have displayed massive improvements in reason- ing and decision-making skills and can hold natural conversations with users. Recently, many tool-use benchmark datasets have been proposed. However, existing datasets have the following limitations: (1). Insufficient evalua…

2024

DDK: Distilling Domain Knowledge for Efficient Large Language Models

NeurIPS 2024poster

Despite the advanced intelligence abilities of large language models (LLMs) in various applications, they still face significant computational and storage demands. Knowledge Distillation (KD) has emerged as an effective strategy to improve the performance of a smaller LLM (i.e., the student model)…

Cited by 10SourcePDFScholar
2024

NeRF-VPT: Learning Novel View Representations with Neural Radiance Fields via View Prompt Tuning

AAAI 2024technical

Neural Radiance Fields (NeRF) have garnered remarkable success in novel view synthesis. Nonetheless, the task of generating high-quality images for novel views persists as a critical challenge. While the existing efforts have exhibited commendable progress, capturing intricate details, enhancing tex…