The seed papers for the winter semester 2026/27 will be released soon.
Seed Papers
Below is a list of papers that can be used as seeds for the seminar. They are loosely categorized for your convenience. You can also suggest papers not listed here if you believe they fit the domain of AI4CA.
Upon acceptance, you will be assigned one seed paper. Use it as a starting point to understand the topic you are working on and find related and more up-to-date papers. For this, you can use the following means:
- Search engines such as Google Scholar, Semantic Scholar, or DBLP.
- Tools such as Connected Papers or Papers With Code.
- Homepages of relevant conferences or researchers (e.g., looking up the authors and conference of your seed paper to see what else they have published).
Evaluation
- What’s Wrong with Your Code Generated by Large Language Models? An Extensive Study
- CROSSCODEEVAL: A Diverse and Multilingual Benchmark for Cross-File Code Completion
- Top Leaderboard Ranking = Top Coding Proficiency, Always? EVOEVAL: Evolving Coding Benchmarks via LLM
- EffiBench: Benchmarking the Efficiency of Automatically Generated Code
- (EvalPerf) Evaluating Language Models for Efficient Code Generation
- BaxBench: Can LLMs Generate Correct and Secure Backends?
Transformer Architectures
- Language-Agnostic Representation Learning of Source Code from Structure and Context
- Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy
Graph Architectures
- Large Language Models on Graphs: A Comprehensive Survey
- Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
- GALLa: Graph Aligned Large Language Models for Improved Source Code Understanding
- CodeGRAG: Bridging the Gap between Natural Language and Programming Language via Graphical Retrieval Augmented Generation
- GraphGPT: Graph Instruction Tuning for Large Language Models
- GraphLLM: Boosting Graph Reasoning Ability of Large Language Model
- Rethinking Positional Encoding in Tree Transformer for Code Representation
- (GoT) Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought
- (GraphGen4Code) A Toolkit for Generating Code Knowledge Graphs
Diffusion Language Models
- (DiffuMamba) DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone
- (DiffuCoder) DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
- (CDC) Constrained Code Generation with Discrete Diffusion
- InfoDLM: an Information-Adaptive Framework for Discrete Diffusion Language Model Pretraining
- Infinite Mask Diffusion for Few-Step Distillation
Efficient Architectures
- SMM Transformer: Leveraging Spiking Neural Networks for Multimodal Tasks
- WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
- UltraLIF: Fully Differentiable Spiking Neural Networks via Ultradiscretization and Max-Plus Algebra
- Caracal: Causal Architecture via Spectral Mixing
Representation Learning (Embeddings)
- (GraphCodeBERT) GraphCodeBERT: Pre-training Code Representations with Data Flow
Code Understanding
Code Generation
- RepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code Completion
- ChopChop: a Programmable Framework for Semantically Constraining the Output of Language Models