Papers Text Generation
“Text Generation” 태그가 달린 논문 6,012편 · 필터 해제
LLM-as-Jev: LLMs Are Already Jev-Style Decision Models -- When and How to Fine-Tune Them
Jev-style decision models return categorical probability distributions over predefined options without generating free-form text, enabling software systems to act on their outputs directly. In this work, we investigate t…
Text GenerationVideo Generation Models: A Survey of Post-Training and Alignment
Video generation has rapidly progressed from short, low-quality clips to high-resolution, long-duration sequences with complex spatiotemporal dynamics. Despite strong generative priors learned through large-scale pretrai…
Video GenerationText GenerationReceiver-Conditioned Latent Communication gives 94% CacheBack
Multi-agent systems distribute large contexts across agents that communicate to solve a task. Text messages are compact but require decoding and may omit evidence the receiving agent needs. Recent latent communication in…
Text GenerationFLEET: From Logits Entropy to Enhanced Trajectories in Text Generation
Solutions based on large language models (LLMs) often rely on temperature sampling to improve accuracy and stability by aggregating multiple samples from the completion distribution. However, this memoryless approach is …
Text GenerationFlash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs
Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregressive LLMs by enabling non-autoregressive text generation. However, their practical deployment remains limited by ineff…
Mathematical ReasoningText GenerationTarget-Language Generation in Multilingual Models: Activation Steering and Optimal Control
Ensuring that multilingual language models generate coherent text in a specific target language is a major issue in multilingual language modeling. We develop an optimal control method for target-language text generation…
Text GenerationViD: Vision-Dominant Gender Bias Mitigation for Large Vision-Language Models
Gender bias in large vision-language models (LVLMs) undermines their fairness and reliability, compromising output trustworthiness. Current mitigation methods rely on training-phase adjustments or post-hoc calibration, b…
Visual GroundingImage CaptioningText GenerationPLUME: Parameter-Efficient Personalization of Large Language Models via Low-Rank User Modulation in Shared Subspaces
Personalizing large language models (LLMs) is essential for delivering AI assistance that aligns with individual users' styles, intents, and preferences. While per-user fine-tuning can substantially enhance personalizati…
Text GenerationWhat Did I Just Say? Self-Listening for Full-Duplex Speech Models
Full-duplex spoken language models can listen and speak simultaneously, enabling them to handle interruptions and backchannels in human conversation. However, text generation, speech synthesis, and audio playback proceed…
Speech SynthesisText GenerationRedEvoAgent: Automatic Red-Teaming Agent with Experience-Driven Skill Evolution
LLM-based agents are increasingly deployed in product-level execution harnesses, where jailbreaks can trigger harmful tool use and persistent state changes, creating greater risks than unsafe text generation alone. Exist…
Text GenerationOverview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models
In 2026, we held the fourth iteration of the SHROOM Shared Task series: SHROOM-Visions (\textbf{S}hared-task on \textbf{H}allucinations and \textbf{R}elated \textbf{O}bservable \textbf{O}vergeneration \textbf{M}istakes i…
Image CaptioningText GenerationLITERARYBIGFIVE: Author-Personalized Text Generation in a Unified Interpretable Space
Personalized text generation for authors and literary writing is essential for applications such as adaptive writing assistants, creative support tools, and computational literary analysis. However, existing approaches t…
Text GenerationThe Illusion of Control: Why Bare Classifier Inversion Silently Fails in Concept-Bottleneck Text Generation
Concept-bottleneck controllable generation routes multi-attribute control through a low-dimensional concept code that, at deployment, must be synthesised from a target attribute configuration. We study this problem in co…
Text GenerationAraDetox: A Multi-Dialect Arabic Detoxification Dataset
Arabic harmful-language detection has received considerable attention, yet Arabic text detoxification remains underexplored. We introduce AraDetox, a multi-dialect Arabic detoxification dataset comprising 10,500 harmful …
Semantic SimilarityText GenerationDon't Repeat Yourself: Stopping Verbatim Loops at Sampling Time
Large Language Models generate text autoregressively, but open-ended generation is prone to verbatim looping, in which models repeat spans already present in context. Standard defenses such as repetition, presence, and f…
Text GenerationFree-Text Evaluation of LLMs for 5G Domain Knowledge and Fault Analysis using LLM-as-Judge
Real-world fault analysis in 5G and emerging 6G networks demands domain expertise to analyze free-text diagnostics, including root-cause explanations and recommended actions. LLMs have emerged as a promising approach to …
Fault DiagnosisText GenerationDiscrete Diffusion Inference-Time Control with Nested Sequential Monte Carlo
We study inference-time control for text generation in discrete diffusion language models, where the goal is to steer sampling toward sequence-level rewards without retraining. Prior work in this domain has focused on pa…
Text GenerationPersonalBench: Measuring the Authorship Gap in LLM Personalization
Personalized text generation aims to make LLMs write in a specific individual's style, yet existing benchmarks measure task accuracy or preference alignment rather than whether the model's output actually resembles the t…
Text GenerationForking Fast: Efficiently Estimating Uncertainty Dynamics in Text Generation
LLM reasoning is stochastic, and so understanding a model requires grappling with the distribution of reasoning chains that it might produce for a given question, i.e., its uncertainty. Resampling-based analyses characte…
Text GenerationEffects of Answer Format Variation on Gender Bias in Large Language Models
Gender bias or other social biases in large language models (LLMs) are frequently evaluated with question answering or survey benchmarks where the LLM needs to give a response in a predefined answer format. It is well kn…
Question AnsweringText Generation