Grammar-constrained decoding enables a new jailbreak (CodeSpear) on LLMs for malicious code, countered by CodeShield which trains models to output harmless honeypot code under GCD while preserving refusals.
Beyond autoregression: An empirical study of diffusion large language models for code generation
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Cola DLM proposes a hierarchical latent diffusion model that learns a text-to-latent mapping, fits a global semantic prior in continuous space with a block-causal DiT, and performs conditional decoding, establishing latent prior modeling as an alternative to token-level autoregressive language model
MEMCoder boosts LLM code generation for private libraries by 16.31% pass@1 via a multi-dimensional evolving memory that distills usage guidelines from execution feedback and combines them with static docs.
citing papers explorer
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Grammar-Constrained Decoding Can Jailbreak LLMs into Generating Malicious Code
Grammar-constrained decoding enables a new jailbreak (CodeSpear) on LLMs for malicious code, countered by CodeShield which trains models to output harmless honeypot code under GCD while preserving refusals.
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Continuous Latent Diffusion Language Model
Cola DLM proposes a hierarchical latent diffusion model that learns a text-to-latent mapping, fits a global semantic prior in continuous space with a block-causal DiT, and performs conditional decoding, establishing latent prior modeling as an alternative to token-level autoregressive language model
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MEMCoder: Multi-dimensional Evolving Memory for Private-Library-Oriented Code Generation
MEMCoder boosts LLM code generation for private libraries by 16.31% pass@1 via a multi-dimensional evolving memory that distills usage guidelines from execution feedback and combines them with static docs.