{"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":"/method/align/papers/4","list_of":"/method/align","method":"ALIGN","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":4,"pages_in_order":56,"rows_per_page":100,"rows":[301,400],"of":5524,"counts":{"archive_papers_tagged":5527,"with_a_code_link":2162,"where_syntology_ran_a_sample":726,"not_listed_spam_title":3,"listed":5524,"listed_where_code_ran":726,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":628,"every_run_a_failure_of_syntologys_instrument":98,"listed_with_a_run_with_no_instrument_failure":628,"listed_every_run_a_failure_of_syntologys_instrument":98,"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":"/method/align","prev":"/method/align/papers/3","next":"/method/align/papers/5","papers":[{"paper":null,"slug":"high-order-equivariant-flow-matching-for","title":"High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Prediction","date":"2025-05-24","arxiv_id":"2505.18817","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-ad-matching-via-cluster-adaptive","title":"Improving Ad matching via Cluster-Adaptive Keyword Expansion and Relevance tuning","date":"2025-05-24","arxiv_id":"2505.18897","n_code_links":0,"syntology":null},{"paper":null,"slug":"metatextgrad-automatically-optimizing","title":"metaTextGrad: Automatically optimizing language model optimizers","date":"2025-05-24","arxiv_id":"2505.18524","n_code_links":0,"syntology":null},{"paper":null,"slug":"response-uncertainty-and-probe-modeling-two","title":"Response Uncertainty and Probe Modeling: Two Sides of the Same Coin in LLM Interpretability?","date":"2025-05-24","arxiv_id":"2505.18575","n_code_links":0,"syntology":null},{"paper":null,"slug":"rolerag-enhancing-llm-role-playing-via-graph","title":"RoleRAG: Enhancing LLM Role-Playing via Graph Guided Retrieval","date":"2025-05-24","arxiv_id":"2505.18541","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-supervised-and-generalizable","title":"Self-Supervised and Generalizable Tokenization for CLIP-Based 3D Understanding","date":"2025-05-24","arxiv_id":"2505.18819","n_code_links":0,"syntology":null},{"paper":null,"slug":"alignment-and-safety-of-diffusion-models-via","title":"Alignment and Safety of Diffusion Models via Reinforcement Learning and Reward Modeling: A Survey","date":"2025-05-23","arxiv_id":"2505.17352","n_code_links":0,"syntology":null},{"paper":null,"slug":"dtrt-enhancing-human-intent-estimation-and","title":"DTRT: Enhancing Human Intent Estimation and Role Allocation for Physical Human-Robot Collaboration","date":"2025-05-23","arxiv_id":"2505.17490","n_code_links":0,"syntology":null},{"paper":null,"slug":"elspr-evaluator-llm-training-data-self","title":"ELSPR: Evaluator LLM Training Data Self-Purification on Non-Transitive Preferences via Tournament Graph Reconstruction","date":"2025-05-23","arxiv_id":"2505.17691","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-adversarial-robustness-of-vision","title":"Enhancing Adversarial Robustness of Vision Language Models via Adversarial Mixture Prompt Tuning","date":"2025-05-23","arxiv_id":"2505.17509","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-it-bad-to-work-all-the-time-cross-cultural","title":"Is It Bad to Work All the Time? Cross-Cultural Evaluation of Social Norm Biases in GPT-4","date":"2025-05-23","arxiv_id":"2505.18322","n_code_links":0,"syntology":null},{"paper":null,"slug":"mmmg-a-comprehensive-and-reliable-evaluation","title":"MMMG: a Comprehensive and Reliable Evaluation Suite for Multitask Multimodal Generation","date":"2025-05-23","arxiv_id":"2505.17613","n_code_links":0,"syntology":null},{"paper":null,"slug":"ownership-verification-of-dnn-models-using","title":"Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation","date":"2025-05-23","arxiv_id":"2505.17579","n_code_links":0,"syntology":null},{"paper":null,"slug":"plan-r1-safe-and-feasible-trajectory-planning","title":"Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling","date":"2025-05-23","arxiv_id":"2505.17659","n_code_links":0,"syntology":null},{"paper":null,"slug":"slot-mllm-object-centric-visual-tokenization","title":"Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM","date":"2025-05-23","arxiv_id":"2505.17726","n_code_links":0,"syntology":null},{"paper":"/paper/taming-diffusion-for-dataset-distillation","slug":"taming-diffusion-for-dataset-distillation","title":"Taming Diffusion for Dataset Distillation with High Representativeness","date":"2025-05-23","arxiv_id":"2505.18399","n_code_links":1,"syntology":{"ran":4,"of":6,"n_ran_checked":2,"n_instrument":2,"unverified":2,"pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["lin-zhao-resolve/d3hr"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/token-reduction-should-go-beyond-efficiency","slug":"token-reduction-should-go-beyond-efficiency","title":"Token Reduction Should Go Beyond Efficiency in Generative Models -- From Vision, Language to Multimodality","date":"2025-05-23","arxiv_id":"2505.18227","n_code_links":1,"syntology":null},{"paper":"/paper/transdf-time-series-forecasting-needs","slug":"transdf-time-series-forecasting-needs","title":"TransDF: Time-Series Forecasting Needs Transformed Label Alignment","date":"2025-05-23","arxiv_id":"2505.17847","n_code_links":0,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":null}},{"paper":null,"slug":"a-novel-generative-model-with-causality","title":"A Novel Generative Model with Causality Constraint for Mitigating Biases in Recommender Systems","date":"2025-05-22","arxiv_id":"2505.16708","n_code_links":0,"syntology":null},{"paper":null,"slug":"decoupledesc-enhancing-emotional-support","title":"DecoupledESC: Enhancing Emotional Support Generation via Strategy-Response Decoupled Preference Optimization","date":"2025-05-22","arxiv_id":"2505.16995","n_code_links":0,"syntology":null},{"paper":"/paper/deep-mineralogical-segmentation-of-thin","slug":"deep-mineralogical-segmentation-of-thin","title":"Deep mineralogical segmentation of thin section images based on QEMSCAN maps","date":"2025-05-22","arxiv_id":"2505.17008","n_code_links":1,"syntology":null},{"paper":null,"slug":"dynamic-sampling-that-adapts-iterative-dpo","title":"Dynamic Sampling that Adapts: Iterative DPO for Self-Aware Mathematical Reasoning","date":"2025-05-22","arxiv_id":"2505.16176","n_code_links":0,"syntology":null},{"paper":"/paper/flow-matching-based-sequential-recommender","slug":"flow-matching-based-sequential-recommender","title":"Flow Matching based Sequential Recommender Model","date":"2025-05-22","arxiv_id":"2505.16298","n_code_links":1,"syntology":{"ran":6,"of":8,"n_ran_checked":6,"n_instrument":0,"unverified":2,"pointer_only":8,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["fengliu-1/fmrec"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"from-generic-empathy-to-personalized","title":"From Generic Empathy to Personalized Emotional Support: A Self-Evolution Framework for User Preference Alignment","date":"2025-05-22","arxiv_id":"2505.16610","n_code_links":0,"syntology":null},{"paper":"/paper/sae-ssv-supervised-steering-in-sparse","slug":"sae-ssv-supervised-steering-in-sparse","title":"SAE-SSV: Supervised Steering in Sparse Representation Spaces for Reliable Control of Language Models","date":"2025-05-22","arxiv_id":"2505.16188","n_code_links":0,"syntology":{"ran":5,"of":5,"n_ran_checked":3,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"5 ran (of which 2 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"unsupervised-prompting-for-graph-neural","title":"Unsupervised Prompting for Graph Neural Networks","date":"2025-05-22","arxiv_id":"2505.16903","n_code_links":0,"syntology":null},{"paper":"/paper/your-pre-trained-llm-is-secretly-an","slug":"your-pre-trained-llm-is-secretly-an","title":"Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator","date":"2025-05-22","arxiv_id":"2505.16690","n_code_links":0,"syntology":{"ran":5,"of":7,"n_ran_checked":5,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":null,"slug":"aln-p3-unified-language-alignment-for","title":"ALN-P3: Unified Language Alignment for Perception, Prediction, and Planning in Autonomous Driving","date":"2025-05-21","arxiv_id":"2505.15158","n_code_links":0,"syntology":null},{"paper":null,"slug":"analyzing-hierarchical-structure-in-vision","title":"Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders","date":"2025-05-21","arxiv_id":"2505.15970","n_code_links":0,"syntology":null},{"paper":null,"slug":"banditspec-adaptive-speculative-decoding-via","title":"BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms","date":"2025-05-21","arxiv_id":"2505.15141","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-the-visual-feature-space-for","slug":"exploring-the-visual-feature-space-for","title":"Exploring The Visual Feature Space for Multimodal Neural Decoding","date":"2025-05-21","arxiv_id":"2505.15755","n_code_links":0,"syntology":{"ran":4,"of":4,"n_ran_checked":4,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 3 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"from-tokens-to-thoughts-how-llms-and-humans","title":"From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning","date":"2025-05-21","arxiv_id":"2505.17117","n_code_links":0,"syntology":null},{"paper":null,"slug":"gama-disentangled-geometric-alignment-with","title":"GAMA++: Disentangled Geometric Alignment with Adaptive Contrastive Perturbation for Reliable Domain Transfer","date":"2025-05-21","arxiv_id":"2505.15241","n_code_links":0,"syntology":null},{"paper":null,"slug":"gt-2-gs-geometry-aware-texture-transfer-for","title":"GT^2-GS: Geometry-aware Texture Transfer for Gaussian Splatting","date":"2025-05-21","arxiv_id":"2505.15208","n_code_links":0,"syntology":null},{"paper":null,"slug":"human-centered-interactive-learning-via-mllms-1","title":"Human-centered Interactive Learning via MLLMs for Text-to-Image Person Re-identification","date":"2025-05-21","arxiv_id":"2506.11036","n_code_links":0,"syntology":null},{"paper":"/paper/meta-design-matters-a-self-design-multi-agent","slug":"meta-design-matters-a-self-design-multi-agent","title":"Meta-Design Matters: A Self-Design Multi-Agent System","date":"2025-05-21","arxiv_id":"2505.14996","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":null}},{"paper":"/paper/on-the-creation-of-narrow-ai-hierarchy-and","slug":"on-the-creation-of-narrow-ai-hierarchy-and","title":"On the creation of narrow AI: hierarchy and nonlocality of neural network skills","date":"2025-05-21","arxiv_id":"2505.15811","n_code_links":1,"syntology":null},{"paper":"/paper/prompt-tuning-vision-language-models-with","slug":"prompt-tuning-vision-language-models-with","title":"Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts","date":"2025-05-21","arxiv_id":"2505.15506","n_code_links":1,"syntology":null},{"paper":null,"slug":"protoknowledge-shapes-behaviour-of-llms-in","title":"Protoknowledge Shapes Behaviour of LLMs in Downstream Tasks: Memorization and Generalization with Knowledge Graphs","date":"2025-05-21","arxiv_id":"2505.15501","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-relevance-feedback-for-interactive","title":"Robust Relevance Feedback for Interactive Known-Item Video Search","date":"2025-05-21","arxiv_id":"2505.15128","n_code_links":0,"syntology":null},{"paper":null,"slug":"slmeval-entropy-based-calibration-for-human","title":"SLMEval: Entropy-Based Calibration for Human-Aligned Evaluation of Large Language Models","date":"2025-05-21","arxiv_id":"2505.16003","n_code_links":0,"syntology":null},{"paper":"/paper/toward-informed-av-decision-making","slug":"toward-informed-av-decision-making","title":"Toward Informed AV Decision-Making: Computational Model of Well-being and Trust in Mobility","date":"2025-05-21","arxiv_id":"2505.14983","n_code_links":1,"syntology":null},{"paper":"/paper/viqagent-zero-shot-video-question-answering","slug":"viqagent-zero-shot-video-question-answering","title":"ViQAgent: Zero-Shot Video Question Answering via Agent with Open-Vocabulary Grounding Validation","date":"2025-05-21","arxiv_id":"2505.15928","n_code_links":1,"syntology":null},{"paper":null,"slug":"audiojailbreak-jailbreak-attacks-against-end","title":"AudioJailbreak: Jailbreak Attacks against End-to-End Large Audio-Language Models","date":"2025-05-20","arxiv_id":"2505.14103","n_code_links":0,"syntology":null},{"paper":null,"slug":"clapfm-evc-high-fidelity-and-flexible","title":"ClapFM-EVC: High-Fidelity and Flexible Emotional Voice Conversion with Dual Control from Natural Language and Speech","date":"2025-05-20","arxiv_id":"2505.13805","n_code_links":0,"syntology":null},{"paper":null,"slug":"context-reasoner-incentivizing-reasoning","title":"Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning","date":"2025-05-20","arxiv_id":"2505.14585","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-domain-diffusion-with-progressive","title":"Cross-Domain Diffusion with Progressive Alignment for Efficient Adaptive Retrieval","date":"2025-05-20","arxiv_id":"2505.13907","n_code_links":0,"syntology":null},{"paper":null,"slug":"divide-by-question-conquer-by-agent-split-rag","title":"Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning","date":"2025-05-20","arxiv_id":"2505.13994","n_code_links":0,"syntology":null},{"paper":"/paper/diving-into-the-fusion-of-monocular-priors","slug":"diving-into-the-fusion-of-monocular-priors","title":"Diving into the Fusion of Monocular Priors for Generalized Stereo Matching","date":"2025-05-20","arxiv_id":"2505.14414","n_code_links":1,"syntology":null},{"paper":"/paper/egocentric-action-aware-inertial-localization","slug":"egocentric-action-aware-inertial-localization","title":"Egocentric Action-aware Inertial Localization in Point Clouds","date":"2025-05-20","arxiv_id":"2505.14346","n_code_links":1,"syntology":null},{"paper":null,"slug":"enhanced-multimodal-aspect-based-sentiment","title":"Enhanced Multimodal Aspect-Based Sentiment Analysis by LLM-Generated Rationales","date":"2025-05-20","arxiv_id":"2505.14499","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-learned-knowledge-in-lora-adapters","title":"Enhancing Learned Knowledge in LoRA Adapters Through Efficient Contrastive Decoding on Ascend NPUs","date":"2025-05-20","arxiv_id":"2505.14620","n_code_links":0,"syntology":null},{"paper":"/paper/improve-language-model-and-brain-alignment","slug":"improve-language-model-and-brain-alignment","title":"Improve Language Model and Brain Alignment via Associative Memory","date":"2025-05-20","arxiv_id":"2505.13844","n_code_links":1,"syntology":null},{"paper":"/paper/infifpo-implicit-model-fusion-via-preference","slug":"infifpo-implicit-model-fusion-via-preference","title":"InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models","date":"2025-05-20","arxiv_id":"2505.13878","n_code_links":1,"syntology":null},{"paper":"/paper/intra-class-patch-swap-for-self-distillation","slug":"intra-class-patch-swap-for-self-distillation","title":"Intra-class Patch Swap for Self-Distillation","date":"2025-05-20","arxiv_id":"2505.14124","n_code_links":1,"syntology":null},{"paper":null,"slug":"moralise-a-structured-benchmark-for-moral","title":"MORALISE: A Structured Benchmark for Moral Alignment in Visual Language Models","date":"2025-05-20","arxiv_id":"2505.14728","n_code_links":0,"syntology":null},{"paper":"/paper/physics-guided-learning-of-meteorological","slug":"physics-guided-learning-of-meteorological","title":"Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting","date":"2025-05-20","arxiv_id":"2505.14555","n_code_links":1,"syntology":null},{"paper":null,"slug":"reward-reasoning-model","title":"Reward Reasoning Model","date":"2025-05-20","arxiv_id":"2505.14674","n_code_links":0,"syntology":null},{"paper":null,"slug":"structured-agent-distillation-for-large","title":"Structured Agent Distillation for Large Language Model","date":"2025-05-20","arxiv_id":"2505.13820","n_code_links":0,"syntology":null},{"paper":null,"slug":"toward-effective-reinforcement-learning-fine","title":"Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models","date":"2025-05-20","arxiv_id":"2505.13973","n_code_links":0,"syntology":null},{"paper":"/paper/towards-verifiability-of-total-value-locked","slug":"towards-verifiability-of-total-value-locked","title":"Towards Verifiability of Total Value Locked (TVL) in Decentralized Finance","date":"2025-05-20","arxiv_id":"2505.14565","n_code_links":1,"syntology":null},{"paper":null,"slug":"aligning-trustworthy-ai-with-democracy-a-dual","title":"Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Risks","date":"2025-05-19","arxiv_id":"2505.13565","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-based-clustering","title":"Attention-based clustering","date":"2025-05-19","arxiv_id":"2505.13112","n_code_links":0,"syntology":null},{"paper":"/paper/beyond-semantics-the-unreasonable","slug":"beyond-semantics-the-unreasonable","title":"Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens","date":"2025-05-19","arxiv_id":"2505.13775","n_code_links":1,"syntology":null},{"paper":null,"slug":"bias-fitting-to-mitigate-length-bias-of","title":"Bias Fitting to Mitigate Length Bias of Reward Model in RLHF","date":"2025-05-19","arxiv_id":"2505.12843","n_code_links":0,"syntology":null},{"paper":"/paper/cross-lingual-representation-alignment","slug":"cross-lingual-representation-alignment","title":"Cross-Lingual Representation Alignment Through Contrastive Image-Caption Tuning","date":"2025-05-19","arxiv_id":"2505.13628","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["nkrasner/cl-clip-align"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":null,"slug":"deep-unfolding-with-kernel-based-quantization","title":"Deep Unfolding with Kernel-based Quantization in MIMO Detection","date":"2025-05-19","arxiv_id":"2505.12736","n_code_links":0,"syntology":null},{"paper":"/paper/degradation-aware-feature-perturbation-for","slug":"degradation-aware-feature-perturbation-for","title":"Degradation-Aware Feature Perturbation for All-in-One Image Restoration","date":"2025-05-19","arxiv_id":"2505.12630","n_code_links":1,"syntology":{"ran":6,"of":7,"n_ran_checked":6,"n_instrument":0,"unverified":1,"pointer_only":7,"phrase":"6 ran (of which 6 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 6 samples that ran constructed an object rather than computing a result","official":{"repos":["txphome/dfpir"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":6,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"event-driven-dynamic-scene-depth-completion","title":"Event-Driven Dynamic Scene Depth Completion","date":"2025-05-19","arxiv_id":"2505.13279","n_code_links":0,"syntology":null},{"paper":null,"slug":"feedback-driven-dynamical-model-for-axonal","title":"Feedback-Driven Dynamical Model for Axonal Extension on Parallel Micropatterns","date":"2025-05-19","arxiv_id":"2505.13361","n_code_links":0,"syntology":null},{"paper":null,"slug":"guidedmorph-two-stage-deformable-registration","title":"GuidedMorph: Two-Stage Deformable Registration for Breast MRI","date":"2025-05-19","arxiv_id":"2505.13414","n_code_links":0,"syntology":null},{"paper":"/paper/improving-compositional-generation-with","slug":"improving-compositional-generation-with","title":"Improving Compositional Generation with Diffusion Models Using Lift Scores","date":"2025-05-19","arxiv_id":"2505.13740","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-multilingual-language-models-by","title":"Improving Multilingual Language Models by Aligning Representations through Steering","date":"2025-05-19","arxiv_id":"2505.12584","n_code_links":0,"syntology":null},{"paper":null,"slug":"measuring-the-faithfulness-of-thinking-drafts","title":"Measuring the Faithfulness of Thinking Drafts in Large Reasoning Models","date":"2025-05-19","arxiv_id":"2505.13774","n_code_links":0,"syntology":null},{"paper":null,"slug":"psymem-fine-grained-psychological-alignment","title":"PsyMem: Fine-grained psychological alignment and Explicit Memory Control for Advanced Role-Playing LLMs","date":"2025-05-19","arxiv_id":"2505.12814","n_code_links":0,"syntology":null},{"paper":"/paper/recollection-from-pensieve-novel-view","slug":"recollection-from-pensieve-novel-view","title":"Recollection from Pensieve: Novel View Synthesis via Learning from Uncalibrated Videos","date":"2025-05-19","arxiv_id":"2505.13440","n_code_links":1,"syntology":null},{"paper":null,"slug":"recommender-systems-for-democracy-toward","title":"Recommender Systems for Democracy: Toward Adversarial Robustness in Voting Advice Applications","date":"2025-05-19","arxiv_id":"2505.13329","n_code_links":0,"syntology":null},{"paper":null,"slug":"recon-robust-symmetry-discovery-via-explicit","title":"RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization","date":"2025-05-19","arxiv_id":"2505.13289","n_code_links":0,"syntology":null},{"paper":null,"slug":"representation-of-perceived-prosodic","title":"Representation of perceived prosodic similarity of conversational feedback","date":"2025-05-19","arxiv_id":"2505.13268","n_code_links":0,"syntology":null},{"paper":null,"slug":"scsiameseclu-a-siamese-clustering-framework","title":"scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data","date":"2025-05-19","arxiv_id":"2505.12626","n_code_links":0,"syntology":null},{"paper":null,"slug":"spklip-aligning-spike-video-streams-with","title":"SPKLIP: Aligning Spike Video Streams with Natural Language","date":"2025-05-19","arxiv_id":"2505.12656","n_code_links":0,"syntology":null},{"paper":null,"slug":"wikipersonas-what-can-we-learn-from","title":"WikiPersonas: What Can We Learn From Personalized Alignment to Famous People?","date":"2025-05-19","arxiv_id":"2505.13257","n_code_links":0,"syntology":null},{"paper":null,"slug":"discovering-interpretable-concepts-in-large","title":"Discovering Interpretable Concepts in Large Generative Music Models","date":"2025-05-18","arxiv_id":"2505.18186","n_code_links":0,"syntology":null},{"paper":null,"slug":"enforcing-fairness-where-it-matters-an","title":"Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints","date":"2025-05-18","arxiv_id":"2505.12530","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaloop-assessing-llm-robustness-in","title":"EVALOOP: Assessing LLM Robustness in Programming from a Self-consistency Perspective","date":"2025-05-18","arxiv_id":"2505.12185","n_code_links":0,"syntology":null},{"paper":null,"slug":"joint-embedding-vs-reconstruction-provable","title":"Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self Supervised Learning","date":"2025-05-18","arxiv_id":"2505.12477","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-to-program-quantum-measurements-for","title":"Learning to Program Quantum Measurements for Machine Learning","date":"2025-05-18","arxiv_id":"2505.13525","n_code_links":0,"syntology":null},{"paper":null,"slug":"sentience-quest-towards-embodied-emotionally","title":"Sentience Quest: Towards Embodied, Emotionally Adaptive, Self-Evolving, Ethically Aligned Artificial General Intelligence","date":"2025-05-18","arxiv_id":"2505.12229","n_code_links":0,"syntology":null},{"paper":null,"slug":"table-r1-region-based-reinforcement-learning","title":"Table-R1: Region-based Reinforcement Learning for Table Understanding","date":"2025-05-18","arxiv_id":"2505.12415","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-open-world-generalized-deepfake","title":"Towards Open-world Generalized Deepfake Detection: General Feature Extraction via Unsupervised Domain Adaptation","date":"2025-05-18","arxiv_id":"2505.12339","n_code_links":0,"syntology":null},{"paper":"/paper/truth-neurons","slug":"truth-neurons","title":"Truth Neurons","date":"2025-05-18","arxiv_id":"2505.12182","n_code_links":1,"syntology":null},{"paper":null,"slug":"vggt-slam-dense-rgb-slam-optimized-on-the-sl","title":"VGGT-SLAM: Dense RGB SLAM Optimized on the SL(4) Manifold","date":"2025-05-18","arxiv_id":"2505.12549","n_code_links":0,"syntology":null},{"paper":null,"slug":"vieeg-hierarchical-neural-coding-with-cross","title":"ViEEG: Hierarchical Neural Coding with Cross-Modal Progressive Enhancement for EEG-Based Visual Decoding","date":"2025-05-18","arxiv_id":"2505.12408","n_code_links":0,"syntology":null},{"paper":"/paper/adaptive-gradient-learning-for-spiking-neural","slug":"adaptive-gradient-learning-for-spiking-neural","title":"Adaptive Gradient Learning for Spiking Neural Networks by Exploiting Membrane Potential Dynamics","date":"2025-05-17","arxiv_id":"2505.11863","n_code_links":0,"syntology":{"ran":1,"of":3,"n_ran_checked":1,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":null,"slug":"adversarial-robustness-for-unified-multi","title":"Adversarial Robustness for Unified Multi-Modal Encoders via Efficient Calibration","date":"2025-05-17","arxiv_id":"2505.11895","n_code_links":0,"syntology":null},{"paper":"/paper/residual-feature-integration-is-sufficient-to","slug":"residual-feature-integration-is-sufficient-to","title":"Residual Feature Integration is Sufficient to Prevent Negative Transfer","date":"2025-05-17","arxiv_id":"2505.11771","n_code_links":2,"syntology":null},{"paper":null,"slug":"self-npo-negative-preference-optimization-of","title":"Self-NPO: Negative Preference Optimization of Diffusion Models by Simply Learning from Itself without Explicit Preference Annotations","date":"2025-05-17","arxiv_id":"2505.11777","n_code_links":0,"syntology":null},{"paper":"/paper/unimoco-unified-modality-completion-for","slug":"unimoco-unified-modality-completion-for","title":"UniMoCo: Unified Modality Completion for Robust Multi-Modal Embeddings","date":"2025-05-17","arxiv_id":"2505.11815","n_code_links":1,"syntology":null},{"paper":"/paper/why-not-act-on-what-you-know-unleashing","slug":"why-not-act-on-what-you-know-unleashing","title":"Why Not Act on What You Know? Unleashing Safety Potential of LLMs via Self-Aware Guard Enhancement","date":"2025-05-17","arxiv_id":"2505.12060","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["njunlp/sage"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"2505-10774","title":"Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting","date":"2025-05-16","arxiv_id":"2505.10774","n_code_links":0,"syntology":null}],"record_sha256":"81fdd8cd46e250e7a7976605fa8e3c77330a73993c81afa4defaf930407eb0eb","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}