Papers Program Synthesis
“Program Synthesis” 태그가 달린 논문 538편 · 필터 해제
Mitigating Gender Bias in Code Large Language Models via Model Editing
In recent years, with the maturation of large language model (LLM) technology and the emergence of high-quality programming code datasets, researchers have become increasingly confident in addressing the challenges of pr…
Code Generationknowledge editingLarge Language ModelModel Editing+1Tackling the Abstraction and Reasoning Corpus with Vision Transformers: the Importance of 2D Representation, Positions, and Objects
The Abstraction and Reasoning Corpus (ARC) is a popular benchmark focused on visual reasoning in the evaluation of Artificial Intelligence systems. In its original framing, an ARC task requires solving a program synthesi…
ARCProgram SynthesisVisual ReasoningCan LLMs plan paths with extra hints from solvers?
Large Language Models (LLMs) have shown remarkable capabilities in natural language processing, mathematical problem solving, and tasks related to program synthesis. However, their effectiveness in long-term planning and…
Mathematical Problem-SolvingProgram SynthesisLearning to Solve Abstract Reasoning Problems with Neurosymbolic Program Synthesis and Task Generation
The ability to think abstractly and reason by analogy is a prerequisite to rapidly adapt to new conditions, tackle newly encountered problems by decomposing them, and synthesize knowledge to solve problems comprehensivel…
Feature EngineeringProgram SynthesisMA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions
Reinforcement learning from human feedback (RLHF) has demonstrated effectiveness in aligning large language models (LLMs) with human preferences. However, token-level RLHF suffers from the credit assignment problem over …
Code GenerationDialogue GenerationProgram SynthesisQuestion Answering+3COOL: Efficient and Reliable Chain-Oriented Objective Logic with Neural Networks Feedback Control for Program Synthesis
Program synthesis methods, whether formal or neural-based, lack fine-grained control and flexible modularity, which limits their adaptation to complex software development. These limitations stem from rigid Domain-Specif…
Program SynthesisMechanic Maker: Accessible Game Development Via Symbolic Learning Program Synthesis
Game development is a highly technical practice that traditionally requires programming skills. This serves as a barrier to entry for would-be developers or those hoping to use games as part of their creative expression.…
Program SynthesisMathDSL: A Domain-Specific Language for Concise Mathematical Solutions Via Program Synthesis
We present MathDSL, a Domain-Specific Language (DSL) for mathematical equation solving, which, when deployed in program synthesis models, outperforms state-of-the-art reinforcement-learning-based methods. We also introdu…
Program Synthesisreinforcement-learningReinforcement LearningProof of Thought : Neurosymbolic Program Synthesis allows Robust and Interpretable Reasoning
Large Language Models (LLMs) have revolutionized natural language processing, yet they struggle with inconsistent reasoning, particularly in novel domains and complex logical sequences. This research introduces Proof of …
BenchmarkingFormal LogicMultimodal ReasoningProgram Synthesis+1Combining LLM Code Generation with Formal Specifications and Reactive Program Synthesis
In the past few years, Large Language Models (LLMs) have exploded in usefulness and popularity for code generation tasks. However, LLMs still struggle with accuracy and are unsuitable for high-risk applications without a…
Code GenerationProgram SynthesisAutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing
Recent advancements in automatic code generation using large language models (LLMs) have brought us closer to fully automated secure software development. However, existing approaches often rely on a single agent for cod…
Code GenerationProgram SynthesisAdaptive Language-Guided Abstraction from Contrastive Explanations
Many approaches to robot learning begin by inferring a reward function from a set of human demonstrations. To learn a good reward, it is necessary to determine which features of the environment are relevant before determ…
Program SynthesisStatically Contextualizing Large Language Models with Typed Holes
Large language models (LLMs) have reshaped the landscape of program synthesis. However, contemporary LLM-based code completion systems often hallucinate broken code because they lack appropriate context, particularly whe…
Code CompletionCode GenerationProgram SynthesisH-ARC: A Robust Estimate of Human Performance on the Abstraction and Reasoning Corpus Benchmark
The Abstraction and Reasoning Corpus (ARC) is a visual program synthesis benchmark designed to test challenging out-of-distribution generalization in humans and machines. Since 2019, limited progress has been observed on…
ARCOut-of-Distribution GeneralizationProgram SynthesisProcedural Synthesis of Synthesizable Molecules
Designing synthetically accessible molecules and recommending analogs to unsynthesizable molecules are important problems for accelerating molecular discovery. We reconceptualize both problems using ideas from program sy…
Evolutionary AlgorithmsProgram SynthesisRelational decomposition for program synthesis
We introduce a novel approach to program synthesis that decomposes complex functional tasks into simpler relational synthesis sub-tasks. We demonstrate the effectiveness of our approach using an off-the-shelf inductive l…
Inductive logic programmingProgram SynthesisCan Large Language Models Understand Symbolic Graphics Programs?
Against the backdrop of enthusiasm for large language models (LLMs), there is an urgent need to scientifically assess their capabilities and shortcomings. This is nontrivial in part because it is difficult to find tasks …
Instruction FollowingProgram Synthesish4rm3l: A language for Composable Jailbreak Attack Synthesis
Despite their demonstrated valuable capabilities, state-of-the-art (SOTA) widely deployed large language models (LLMs) still have the potential to cause harm to society due to the ineffectiveness of their safety filters,…
BenchmarkingProgram SynthesisRed TeamingVRDSynth: Synthesizing Programs for Multilingual Visually Rich Document Information Extraction
Businesses need to query visually rich documents (VRDs) like receipts, medical records, and insurance forms to make decisions. Existing techniques for extracting entities from VRDs struggle with new layouts or require ex…
Entity LinkingProgram SynthesisTable RecognitionA Neurosymbolic Approach to Adaptive Feature Extraction in SLAM
Autonomous robots, autonomous vehicles, and humans wearing mixed-reality headsets require accurate and reliable tracking services for safety-critical applications in dynamically changing real-world environments. However,…
Autonomous VehiclesMixed RealityProgram SynthesisSimultaneous Localization and Mapping