Papers Program Synthesis
“Program Synthesis” 태그가 달린 논문 538편 · 필터 해제
CodeUpdateArena: Benchmarking Knowledge Editing on API Updates
Large language models (LLMs) are increasingly being used to synthesize and reason about source code. However, the static nature of these models' knowledge does not reflect the fact that libraries and API functions they i…
Benchmarkingknowledge editingProgram SynthesisEffective Adaptive Mutation Rates for Program Synthesis
The problem-solving performance of many evolutionary algorithms, including genetic programming systems used for program synthesis, depends on the values of hyperparameters including mutation rates. The mutation method us…
Evolutionary AlgorithmsProgram SynthesisSymbolic RegressionBug In the Code Stack: Can LLMs Find Bugs in Large Python Code Stacks
Recent research in Needle-in-a-Haystack (NIAH) benchmarks has explored the capabilities of Large Language Models (LLMs) in retrieving contextual information from large text documents. However, as LLMs become increasingly…
Program SynthesisFVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving
Formal verification (FV) has witnessed growing significance with current emerging program synthesis by the evolving large language models (LLMs). However, current formal verification mainly resorts to symbolic verifiers …
Automated Theorem ProvingProgram SynthesisProgram Synthesis Benchmark for Visual Programming in XLogoOnline Environment
Large language and multimodal models have shown remarkable successes on various benchmarks focused on specific skills such as general-purpose programming, natural language understanding, math word problem-solving, and vi…
Logical ReasoningMathMath Word Problem SolvingNatural Language Understanding+3Learning Language Structures through Grounding
Language is highly structured, with syntactic and semantic structures, to some extent, agreed upon by speakers of the same language. With implicit or explicit awareness of such structures, humans can learn and use langua…
Automatic Speech RecognitionDependency ParsingProgram Synthesisspeech-recognition+3Guiding LLM Temporal Logic Generation with Explicit Separation of Data and Control
Temporal logics are powerful tools that are widely used for the synthesis and verification of reactive systems. The recent progress on Large Language Models (LLMs) has the potential to make the process of writing such sp…
Program SynthesisHow Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark
The emergence of large language models (LLMs) has significantly pushed the frontiers of program synthesis. Advancement of LLM-based program synthesis calls for a thorough evaluation of LLM-generated code. Most evaluation…
HumanEvalProgram SynthesisAmortizing Pragmatic Program Synthesis with Rankings
The usage of Rational Speech Acts (RSA) framework has been successful in building \emph{pragmatic} program synthesizers that return programs which, in addition to being logically consistent with user-generated examples, …
Program SynthesisDiffusion On Syntax Trees For Program Synthesis
Large language models generate code one token at a time. Their autoregressive generation process lacks the feedback of observing the program's output. Training LLMs to suggest edits directly can be challenging due to the…
Program SynthesisAbstractBeam: Enhancing Bottom-Up Program Synthesis using Library Learning
LambdaBeam is a state-of-the-art, execution-guided algorithm for program synthesis that utilizes higher-order functions, lambda functions, and iterative loops within a Domain-Specific Language (DSL). LambdaBeam generates…
Program SynthesisRLSF: Reinforcement Learning via Symbolic Feedback
Reinforcement Learning with Human Feedback (RLHF) is considered a standard approach to fine-tuning Large Language Models (LLMs). However, such methods often face limitations such as unsound black-box reward models, diffi…
Logical ReasoningNatural Language UnderstandingProgram Synthesisreinforcement-learning+1Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
Iteratively improving and repairing source code with large language models (LLMs), known as refinement, has emerged as a popular way of generating programs that would be too complex to construct in one shot. Given a bank…
Code RepairLanguage ModelingLanguage ModellingProgram Synthesis+2Learning to Reason via Program Generation, Emulation, and Search
Program synthesis with language models (LMs) has unlocked a large set of reasoning abilities; code-tuned LMs have proven adept at generating programs that solve a wide variety of algorithmic symbolic manipulation tasks (…
Code GenerationIn-Context LearningProgram SynthesisGenerating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
In this work we consider Code World Models, world models generated by a Large Language Model (LLM) in the form of Python code for model-based Reinforcement Learning (RL). Calling code instead of LLMs for planning has pot…
Code GenerationLanguage ModellingLarge Language ModelModel-based Reinforcement Learning+3HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis
Many structured prediction and reasoning tasks can be framed as program synthesis problems, where the goal is to generate a program in a domain-specific language (DSL) that transforms input data into the desired output. …
Program SynthesisStructured PredictionAnalogical proportions II
Analogical reasoning is the ability to detect parallels between two seemingly distant objects or situations, a fundamental human capacity used for example in commonsense reasoning, learning, and creativity which is belie…
Program SynthesisGoals as Reward-Producing Programs
People are remarkably capable of generating their own goals, beginning with child's play and continuing into adulthood. Despite considerable empirical and computational work on goals and goal-oriented behavior, models ar…
DiversityProgram SynthesisMapCoder: Multi-Agent Code Generation for Competitive Problem Solving
Code synthesis, which requires a deep understanding of complex natural language problem descriptions, generation of code instructions for complex algorithms and data structures, and the successful execution of comprehens…
Code GenerationHumanEvalmbppProgram SynthesisFinding structure in logographic writing with library learning
One hallmark of human language is its combinatoriality -- reusing a relatively small inventory of building blocks to create a far larger inventory of increasingly complex structures. In this paper, we explore the idea th…
Inductive BiasProgram Synthesis