{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/text-generation/papers/22","list_of":"/task/text-generation","task":"Text Generation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":22,"pages_in_order":54,"rows_per_page":100,"rows":[2101,2200],"of":5335,"counts":{"archive_papers_tagged":5335,"with_a_code_link":2047,"where_syntology_ran_a_sample":610,"not_listed_spam_title":0,"listed":5335,"listed_where_code_ran":610,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":503,"every_run_a_failure_of_syntologys_instrument":107,"listed_with_a_run_with_no_instrument_failure":503,"listed_every_run_a_failure_of_syntologys_instrument":107,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/text-generation","prev":"/task/text-generation/papers/21","next":"/task/text-generation/papers/23","papers":[{"url":null,"slug":"resource-for-error-analysis-in-text","title":"Resource for Error Analysis in Text Simplification: New Taxonomy and Test Collection","date":"2025-05-22","arxiv_id":"2505.16392","repositories_listed":0,"syntology":null},{"url":null,"slug":"banditspec-adaptive-speculative-decoding-via","title":"BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms","date":"2025-05-21","arxiv_id":"2505.15141","repositories_listed":0,"syntology":null},{"url":null,"slug":"hallucinate-at-the-last-in-long-response","title":"Hallucinate at the Last in Long Response Generation: A Case Study on Long Document Summarization","date":"2025-05-21","arxiv_id":"2505.15291","repositories_listed":0,"syntology":null},{"url":null,"slug":"reppl-recalibrating-perplexity-by-uncertainty","title":"RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection","date":"2025-05-21","arxiv_id":"2505.15386","repositories_listed":0,"syntology":null},{"url":null,"slug":"creative-preference-optimization","title":"Creative Preference Optimization","date":"2025-05-20","arxiv_id":"2505.14442","repositories_listed":0,"syntology":null},{"url":null,"slug":"ctrldiff-boosting-large-diffusion-language","title":"CtrlDiff: Boosting Large Diffusion Language Models with Dynamic Block Prediction and Controllable Generation","date":"2025-05-20","arxiv_id":"2505.14455","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-jailbreak-attacks-on-llms-through","title":"Exploring Jailbreak Attacks on LLMs through Intent Concealment and Diversion","date":"2025-05-20","arxiv_id":"2505.14316","repositories_listed":0,"syntology":null},{"url":null,"slug":"haet-bhasha-aur-diskrimineshun-phonetic","title":"\"Haet Bhasha aur Diskrimineshun\": Phonetic Perturbations in Code-Mixed Hinglish to Red-Team LLMs","date":"2025-05-20","arxiv_id":"2505.14226","repositories_listed":0,"syntology":null},{"url":null,"slug":"past-phonetic-acoustic-speech-tokenizer","title":"PAST: Phonetic-Acoustic Speech Tokenizer","date":"2025-05-20","arxiv_id":"2505.14470","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-generation-beyond-discrete-token","title":"Text Generation Beyond Discrete Token Sampling","date":"2025-05-20","arxiv_id":"2505.14827","repositories_listed":0,"syntology":null},{"url":null,"slug":"frabench-and-geneval-scaling-fine-grained","title":"FRAbench and GenEval: Scaling Fine-Grained Aspect Evaluation across Tasks, Modalities","date":"2025-05-19","arxiv_id":"2505.12795","repositories_listed":0,"syntology":null},{"url":null,"slug":"guard-generation-time-llm-unlearning-via","title":"GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection","date":"2025-05-19","arxiv_id":"2505.13312","repositories_listed":0,"syntology":null},{"url":null,"slug":"2505-10993","title":"Generative Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges","date":"2025-05-16","arxiv_id":"2505.10993","repositories_listed":0,"syntology":null},{"url":null,"slug":"2505-11336","title":"XtraGPT: LLMs for Human-AI Collaboration on Controllable Academic Paper Revision","date":"2025-05-16","arxiv_id":"2505.11336","repositories_listed":0,"syntology":null},{"url":null,"slug":"2505-11485","title":"Modeling cognitive processes of natural reading with transformer-based Language Models","date":"2025-05-16","arxiv_id":"2505.11485","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-control-for-transformer-architectures","title":"Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency","date":"2025-05-16","arxiv_id":"2505.13499","repositories_listed":0,"syntology":null},{"url":null,"slug":"qronos-correcting-the-past-by-shaping-the","title":"Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization","date":"2025-05-16","arxiv_id":"2505.11695","repositories_listed":0,"syntology":null},{"url":null,"slug":"2505-10634","title":"Cross-Image Contrastive Decoding: Precise, Lossless Suppression of Language Priors in Large Vision-Language Models","date":"2025-05-15","arxiv_id":"2505.10634","repositories_listed":0,"syntology":null},{"url":null,"slug":"moltextnet-a-two-million-molecule-text","title":"MolTextNet: A Two-Million Molecule-Text Dataset for Multimodal Molecular Learning","date":"2025-05-15","arxiv_id":"2506.00009","repositories_listed":0,"syntology":null},{"url":null,"slug":"ultrasound-report-generation-with-multimodal","title":"Ultrasound Report Generation with Multimodal Large Language Models for Standardized Texts","date":"2025-05-13","arxiv_id":"2505.08838","repositories_listed":0,"syntology":null},{"url":null,"slug":"hdglyph-a-hierarchical-disentangled-glyph","title":"HDGlyph: A Hierarchical Disentangled Glyph-Based Framework for Long-Tail Text Rendering in Diffusion Models","date":"2025-05-10","arxiv_id":"2505.06543","repositories_listed":0,"syntology":null},{"url":null,"slug":"insertion-language-models-sequence-generation","title":"Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions","date":"2025-05-09","arxiv_id":"2505.05755","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-two-sample-test-of-text-generation","title":"A Two-Sample Test of Text Generation Similarity","date":"2025-05-08","arxiv_id":"2505.05269","repositories_listed":0,"syntology":null},{"url":null,"slug":"glyphmastero-a-glyph-encoder-for-high","title":"GlyphMastero: A Glyph Encoder for High-Fidelity Scene Text Editing","date":"2025-05-08","arxiv_id":"2505.04915","repositories_listed":0,"syntology":null},{"url":null,"slug":"looking-beyond-language-priors-enhancing","title":"Looking Beyond Language Priors: Enhancing Visual Comprehension and Attention in Multimodal Models","date":"2025-05-08","arxiv_id":"2505.05626","repositories_listed":0,"syntology":null},{"url":null,"slug":"mogao-an-omni-foundation-model-for","title":"Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation","date":"2025-05-08","arxiv_id":"2505.05472","repositories_listed":0,"syntology":null},{"url":null,"slug":"natural-language-generation-in-healthcare-a","title":"Natural Language Generation in Healthcare: A Review of Methods and Applications","date":"2025-05-07","arxiv_id":"2505.04073","repositories_listed":0,"syntology":null},{"url":null,"slug":"procedural-memory-is-not-all-you-need","title":"Procedural Memory Is Not All You Need: Bridging Cognitive Gaps in LLM-Based Agents","date":"2025-05-06","arxiv_id":"2505.03434","repositories_listed":0,"syntology":null},{"url":null,"slug":"survey-of-abstract-meaning-representation","title":"Survey of Abstract Meaning Representation: Then, Now, Future","date":"2025-05-06","arxiv_id":"2505.03229","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-character-based-diffusion-embedding","title":"A Character-based Diffusion Embedding Algorithm for Enhancing the Generation Quality of Generative Linguistic Steganographic Texts","date":"2025-05-02","arxiv_id":"2505.00977","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-rusty-link-in-the-ai-supply-chain-detecting","title":"A Rusty Link in the AI Supply Chain: Detecting Evil Configurations in Model Repositories","date":"2025-05-02","arxiv_id":"2505.01067","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-one-size-fits-all-inversion-learning","title":"Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Prompts","date":"2025-04-29","arxiv_id":"2504.21117","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-synthetic-out-of-distribution-exposure","title":"Graph Synthetic Out-of-Distribution Exposure with Large Language Models","date":"2025-04-29","arxiv_id":"2504.21198","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-gravity-a-field-theoretic-model","title":"Information Gravity: A Field-Theoretic Model for Token Selection in Large Language Models","date":"2025-04-29","arxiv_id":"2504.20951","repositories_listed":0,"syntology":null},{"url":null,"slug":"yochameleon-personalized-vision-and-language","title":"YoChameleon: Personalized Vision and Language Generation","date":"2025-04-29","arxiv_id":"2504.20998","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-platform-for-generating-educational","title":"A Platform for Generating Educational Activities to Teach English as a Second Language","date":"2025-04-28","arxiv_id":"2504.20251","repositories_listed":0,"syntology":null},{"url":null,"slug":"anyprefer-an-agentic-framework-for-preference","title":"Anyprefer: An Agentic Framework for Preference Data Synthesis","date":"2025-04-27","arxiv_id":"2504.19276","repositories_listed":0,"syntology":null},{"url":null,"slug":"trace-back-from-the-future-a-probabilistic","title":"TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation","date":"2025-04-25","arxiv_id":"2504.18535","repositories_listed":0,"syntology":null},{"url":null,"slug":"token-shuffle-towards-high-resolution-image","title":"Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models","date":"2025-04-24","arxiv_id":"2504.17789","repositories_listed":0,"syntology":null},{"url":null,"slug":"distilling-semantically-aware-orders-for","title":"Distilling semantically aware orders for autoregressive image generation","date":"2025-04-23","arxiv_id":"2504.17069","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-effective-are-generative-large-language","title":"How Effective are Generative Large Language Models in Performing Requirements Classification?","date":"2025-04-23","arxiv_id":"2504.16768","repositories_listed":0,"syntology":null},{"url":null,"slug":"im-possibility-of-automated-hallucination","title":"(Im)possibility of Automated Hallucination Detection in Large Language Models","date":"2025-04-23","arxiv_id":"2504.17004","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairsteer-inference-time-debiasing-for-llms","title":"FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering","date":"2025-04-20","arxiv_id":"2504.14492","repositories_listed":0,"syntology":null},{"url":null,"slug":"farseval-pkbets-a-new-diverse-benchmark-for","title":"FarsEval-PKBETS: A new diverse benchmark for evaluating Persian large language models","date":"2025-04-20","arxiv_id":"2504.14690","repositories_listed":0,"syntology":null},{"url":null,"slug":"lgd-leveraging-generative-descriptions-for","title":"LGD: Leveraging Generative Descriptions for Zero-Shot Referring Image Segmentation","date":"2025-04-20","arxiv_id":"2504.14467","repositories_listed":0,"syntology":null},{"url":null,"slug":"density-measures-for-language-generation","title":"Density Measures for Language Generation","date":"2025-04-19","arxiv_id":"2504.14370","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparks-of-science-hypothesis-generation-using","title":"Sparks of Science: Hypothesis Generation Using Structured Paper Data","date":"2025-04-17","arxiv_id":"2504.12976","repositories_listed":0,"syntology":null},{"url":null,"slug":"entropy-guided-watermarking-for-llms-a-test","title":"Entropy-Guided Watermarking for LLMs: A Test-Time Framework for Robust and Traceable Text Generation","date":"2025-04-16","arxiv_id":"2504.12108","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-next-generation-reasoning","title":"Benchmarking Next-Generation Reasoning-Focused Large Language Models in Ophthalmology: A Head-to-Head Evaluation on 5,888 Items","date":"2025-04-15","arxiv_id":"2504.11186","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-action-language-modelling-for","title":"Joint Action Language Modelling for Transparent Policy Execution","date":"2025-04-14","arxiv_id":"2504.10055","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferable-text-data-distillation-by","title":"Transferable text data distillation by trajectory matching","date":"2025-04-14","arxiv_id":"2504.09818","repositories_listed":0,"syntology":null},{"url":null,"slug":"elsa-a-style-aligned-dataset-for-emotionally","title":"ELSA: A Style Aligned Dataset for Emotionally Intelligent Language Generation","date":"2025-04-11","arxiv_id":"2504.08281","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-as-span-annotators","title":"Large Language Models as Span Annotators","date":"2025-04-11","arxiv_id":"2504.08697","repositories_listed":0,"syntology":null},{"url":null,"slug":"medhal-an-evaluation-dataset-for-medical","title":"MedHal: An Evaluation Dataset for Medical Hallucination Detection","date":"2025-04-11","arxiv_id":"2504.08596","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepseek-vs-o3-mini-how-well-can-reasoning","title":"DeepSeek vs. o3-mini: How Well can Reasoning LLMs Evaluate MT and Summarization?","date":"2025-04-10","arxiv_id":"2504.08120","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-data-generation-multi-step-rl-for","title":"Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use","date":"2025-04-07","arxiv_id":"2504.04736","repositories_listed":0,"syntology":null},{"url":null,"slug":"unleashing-the-power-of-llms-in-dense","title":"Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling","date":"2025-04-07","arxiv_id":"2504.05216","repositories_listed":0,"syntology":null},{"url":null,"slug":"align-to-structure-aligning-large-language","title":"Align to Structure: Aligning Large Language Models with Structural Information","date":"2025-04-04","arxiv_id":"2504.03622","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-compact-llms-for-zero-shot-iberian","title":"Evaluating Compact LLMs for Zero-Shot Iberian Language Tasks on End-User Devices","date":"2025-04-04","arxiv_id":"2504.03312","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-don-t-search-rethinking-test-time","title":"Sample, Don't Search: Rethinking Test-Time Alignment for Language Models","date":"2025-04-04","arxiv_id":"2504.03790","repositories_listed":0,"syntology":null},{"url":null,"slug":"stance-driven-multimodal-controlled-statement","title":"Stance-Driven Multimodal Controlled Statement Generation: New Dataset and Task","date":"2025-04-04","arxiv_id":"2504.03295","repositories_listed":0,"syntology":null},{"url":null,"slug":"cola-learning-to-interactively-collaborate","title":"CoLa -- Learning to Interactively Collaborate with Large LMs","date":"2025-04-03","arxiv_id":"2504.02965","repositories_listed":0,"syntology":null},{"url":null,"slug":"pel-a-programming-language-for-orchestrating","title":"Pel, A Programming Language for Orchestrating AI Agents","date":"2025-04-03","arxiv_id":"2505.13453","repositories_listed":0,"syntology":null},{"url":null,"slug":"state-of-the-art-translation-of-text-to-gloss","title":"State-of-the-Art Translation of Text-to-Gloss using mBART : A case study of Bangla","date":"2025-04-03","arxiv_id":"2504.02293","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastscore-towards-higher-quality-less","title":"ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation","date":"2025-04-02","arxiv_id":"2504.02106","repositories_listed":0,"syntology":null},{"url":null,"slug":"lvmed-r2-perception-and-reflection-driven","title":"LVMed-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generation","date":"2025-04-02","arxiv_id":"2504.02885","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-virtual-mixture-of-experts","title":"A Unified Virtual Mixture-of-Experts Framework:Enhanced Inference and Hallucination Mitigation in Single-Model System","date":"2025-04-01","arxiv_id":"2504.03739","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphmaster-automated-graph-synthesis-via-llm","title":"GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments","date":"2025-04-01","arxiv_id":"2504.00711","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-agent-llm-judge-automatic-personalized","title":"Multi-Agent LLM Judge: automatic personalized LLM judge design for evaluating natural language generation applications","date":"2025-04-01","arxiv_id":"2504.02867","repositories_listed":0,"syntology":null},{"url":null,"slug":"repetitions-are-not-all-alike-distinct","title":"Repetitions are not all alike: distinct mechanisms sustain repetition in language models","date":"2025-04-01","arxiv_id":"2504.01100","repositories_listed":0,"syntology":null},{"url":null,"slug":"scholarcopilot-training-large-language-models","title":"ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations","date":"2025-04-01","arxiv_id":"2504.00824","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthesized-annotation-guidelines-are","title":"Synthesized Annotation Guidelines are Knowledge-Lite Boosters for Clinical Information Extraction","date":"2025-04-01","arxiv_id":"2504.02871","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-layer-skipping-in-pre-trained-llms","title":"Adaptive Layer-skipping in Pre-trained LLMs","date":"2025-03-31","arxiv_id":"2503.23798","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-humor-generation-in-large-language","title":"Optimizing Humor Generation in Large Language Models: Temperature Configurations and Architectural Trade-offs","date":"2025-03-31","arxiv_id":"2504.02858","repositories_listed":0,"syntology":null},{"url":null,"slug":"not-all-lora-parameters-are-essential","title":"Not All LoRA Parameters Are Essential: Insights on Inference Necessity","date":"2025-03-30","arxiv_id":"2503.23360","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-deepseek-v3-reason-like-a-surgeon-an","title":"Can DeepSeek Reason Like a Surgeon? An Empirical Evaluation for Vision-Language Understanding in Robotic-Assisted Surgery","date":"2025-03-29","arxiv_id":"2503.23130","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-challenge-of-achieving-attributability-in","title":"The Challenge of Achieving Attributability in Multilingual Table-to-Text Generation with Question-Answer Blueprints","date":"2025-03-29","arxiv_id":"2503.23204","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-reasoning-memorization-interplay-in","title":"The Reasoning-Memorization Interplay in Language Models Is Mediated by a Single Direction","date":"2025-03-29","arxiv_id":"2503.23084","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-mixture-of-experts-redundancy","title":"Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities","date":"2025-03-28","arxiv_id":"2503.22517","repositories_listed":0,"syntology":null},{"url":null,"slug":"cognitive-prompts-using-guilford-s-structure","title":"Cognitive Prompts Using Guilford's Structure of Intellect Model","date":"2025-03-27","arxiv_id":"2503.22036","repositories_listed":0,"syntology":null},{"url":null,"slug":"lex-art-rethinking-text-generation-via","title":"LeX-Art: Rethinking Text Generation via Scalable High-Quality Data Synthesis","date":"2025-03-27","arxiv_id":"2503.21749","repositories_listed":0,"syntology":null},{"url":null,"slug":"local-normalization-distortion-and-the","title":"Local Normalization Distortion and the Thermodynamic Formalism of Decoding Strategies for Large Language Models","date":"2025-03-27","arxiv_id":"2503.21929","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-safe-and-aligned-language","title":"Optimizing Safe and Aligned Language Generation: A Multi-Objective GRPO Approach","date":"2025-03-26","arxiv_id":"2503.21819","repositories_listed":0,"syntology":null},{"url":null,"slug":"kshseek-data-driven-approaches-to-mitigating","title":"KSHSeek: Data-Driven Approaches to Mitigating and Detecting Knowledge-Shortcut Hallucinations in Generative Models","date":"2025-03-25","arxiv_id":"2503.19482","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-llms-automate-fact-checking-article","title":"Can LLMs Automate Fact-Checking Article Writing?","date":"2025-03-22","arxiv_id":"2503.17684","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiscale-contextual-bandits-for-long-term","title":"MultiScale Contextual Bandits for Long Term Objectives","date":"2025-03-22","arxiv_id":"2503.17674","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-consistency-and-reproducibility-in","title":"Assessing Consistency and Reproducibility in the Outputs of Large Language Models: Evidence Across Diverse Finance and Accounting Tasks","date":"2025-03-21","arxiv_id":"2503.16974","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-llm-guardrails-via-sparse","title":"Towards LLM Guardrails via Sparse Representation Steering","date":"2025-03-21","arxiv_id":"2503.16851","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-styled-text-image-generation-but","title":"Zero-Shot Styled Text Image Generation, but Make It Autoregressive","date":"2025-03-21","arxiv_id":"2503.17074","repositories_listed":0,"syntology":null},{"url":null,"slug":"attention2d-communication-efficient","title":"ATTENTION2D: Communication Efficient Distributed Self-Attention Mechanism","date":"2025-03-20","arxiv_id":"2503.15758","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-braces-straightening-out-llm-predictions","title":"LLM Braces: Straightening Out LLM Predictions with Relevant Sub-Updates","date":"2025-03-20","arxiv_id":"2503.16334","repositories_listed":0,"syntology":null},{"url":null,"slug":"natural-language-generation-1","title":"Natural Language Generation","date":"2025-03-20","arxiv_id":"2503.16728","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-quantification-and-confidence-1","title":"Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey","date":"2025-03-20","arxiv_id":"2503.15850","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-on-large-language-models-for-visual","title":"A Review on Large Language Models for Visual Analytics","date":"2025-03-19","arxiv_id":"2503.15176","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancing-deep-learning-through-probability","title":"Advancing Deep Learning through Probability Engineering: A Pragmatic Paradigm for Modern AI","date":"2025-03-19","arxiv_id":"2503.18958","repositories_listed":0,"syntology":null},{"url":null,"slug":"r-2-a-llm-based-novel-to-screenplay","title":"R$^2$: A LLM Based Novel-to-Screenplay Generation Framework with Causal Plot Graphs","date":"2025-03-19","arxiv_id":"2503.15655","repositories_listed":0,"syntology":null},{"url":null,"slug":"trove-a-challenge-for-fine-grained-text","title":"TROVE: A Challenge for Fine-Grained Text Provenance via Source Sentence Tracing and Relationship Classification","date":"2025-03-19","arxiv_id":"2503.15289","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-head-to-tail-towards-balanced","title":"From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration","date":"2025-03-17","arxiv_id":"2503.12821","repositories_listed":0,"syntology":null},{"url":null,"slug":"repa-russian-error-types-annotation-for","title":"REPA: Russian Error Types Annotation for Evaluating Text Generation and Judgment Capabilities","date":"2025-03-17","arxiv_id":"2503.13102","repositories_listed":0,"syntology":null},{"url":null,"slug":"textinvision-text-and-prompt-complexity","title":"TextInVision: Text and Prompt Complexity Driven Visual Text Generation Benchmark","date":"2025-03-17","arxiv_id":"2503.13730","repositories_listed":0,"syntology":null}],"record_sha256":"696edeffb943e461e8d8bf3c3fa93e5368b43513c1d17a5dae95ef7c0194a881","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}