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2023年11月16日日記１時間で資料の第0稿をでっち上げる必要が出た『体験の観察が well-being を向上させる条件　―無執着の観点から―』『新しい計画と管理の技法』論文指導トレイトに関する論文がある卒業論文論文の著作権修士論文論文を書きたくないあれ論文には著作権がある『学術誌や学会誌の論文と著作権について』デライト及び輪郭法を論文にする論文を書くhttp://ymatsuo2.sakura.ne.jp/surveyscript/survey.htm『Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation』輪郭法の論文論文管理高田論文学術論文論文のテンプレート『Object- Oriented User Interfaces and Object-Oriented Languages』あれ論文は結果であって目的ではない論文を読む『ほぼ毎日論文を読んで365日になった！ - noki - Medium』論文執筆『Leveraging Intent Detection and Generative AI for Enhanced Customer Support』『graph-based-deep-learning-literature/conference-publications at master · naganandy/graph-based-deep-learning-literature』Readable論文読み読んだ論文を生成AIに説明する論文博士『Challenges in applying large language models to requirements engineering tasks』『LLM‐based Approach to Automatically Establish Traceability between Requirements and MBSE』『LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead』『大規模言語モデルによる要求仕様書の品質評価』『Natural language processing: state of the art, current trends and challenges』『DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs』『Large Language Models on Graphs: A Comprehensive Survey』『Revisiting Model Stitching to Compare Neural Representations』『Explanatory models in neuroscience: Part 2 – constraint-based intelligibility』『When Do Curricula Work?』『TrendScape 1.0: 言語モデルの潜在空間上の概念探索』『Adversarial Examples Are Not Bugs, They Are Features』『nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models』『Japanese MT-bench++: より自然なマルチターン対話設定の 日本語大規模ベンチマーク』Obsidianの論文『An LLM Compiler for Parallel Function Calling』『Counterfactual Token Generation in Large Language Models』学術雑誌『Temporal Database Management and the Representation of Temporal Dynamics』『作業記憶の発達的特性が言語獲得の臨界期を形成する』『Catastrophic forgetting in connectionist networks』『Overcoming catastrophic forgetting in neural networks』『Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation』『BabyBERTa: Learning More Grammar With Small-Scale Child-Directed Language』『Intelligent Scheduling with Reinforcement Learning』『Distributionally Robust Optimization』『Stochastic model for physician staffing and scheduling in emergency departments with multiple treatment stages』『High-dimensional multi-period portfolio allocation using deep reinforcement learning』『Contrastive Decoding: Open-ended Text Generation as Optimization』『DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts』『Injecting Knowledge Graphs into Large Language Models』『モデル拡張によるパラメータ効率的な LLM の事前学習』『Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position - Fukushima1980.pdf』『Automated Progressive Learning for Efficient Training of Vision Transformers』『Towards Adaptive Residual Network Training: A Neural-ODE Perspective』『GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection』『ReLoRA: High-Rank Training Through Low-Rank Updates』『Multi-level Residual Networks from Dynamical Systems View』