Every paper checked — nothing hidden

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Every paper checked for brief #4 of 12–19 Oct 2026 — nothing is hidden. Brief papers first.

All17,313 In brief24 More (on-topic)3,333 Not relevant13,754 Not assessed87 Older352 Could not confirm93 Blogs with no paper266 All blogs284

Paper	Topic	Relevance
Feedback as an Interface: Controlling Form and Detail in LLM Translation Refinement The paper investigates how varying the detail and format of feedback affects machine translation refinement in large language models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Examines translation accuracy refinement rather than deployment safety hazards.
A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding The paper introduces a Persian vision-language-action dataset and benchmark to evaluate robotic instruction grounding under deliberate ambiguity and infeasibility. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Household robot vision grounding, not industrial quality control inspection.
A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding The paper introduces a Persian vision-language-action dataset and benchmark to evaluate robotic instruction grounding under deliberate ambiguity and infeasibility. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on benchmark creation rather than deployment safety guardrails.
A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding The paper introduces a Persian vision-language-action dataset and benchmark to evaluate robotic instruction grounding under deliberate ambiguity and infeasibility. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not study model compression, distillation, or efficient inference.
A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding The paper introduces a Persian vision-language-action dataset and benchmark to evaluate robotic instruction grounding under deliberate ambiguity and infeasibility. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Focuses on embodied action plans, not software code generation.
A Persian Vision-Language-Action Dataset and Benchmark for Ambiguity- and Infeasibility-Aware Instruction-to-Plan Grounding The paper introduces a Persian vision-language-action dataset and benchmark to evaluate robotic instruction grounding under deliberate ambiguity and infeasibility. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Uses RAG as an ablation baseline, not core focus.
Rate-Resolved Text Evaluation with Masked Diffusion Language Models The paper introduces rate-resolved text evaluation to turn masking rates in diffusion language models into diagnostic scores for text assessment. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not address model compression or efficient serving.
Rate-Resolved Text Evaluation with Masked Diffusion Language Models The paper introduces rate-resolved text evaluation to turn masking rates in diffusion language models into diagnostic scores for text assessment. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Not focused on software code or programming tasks.
Rate-Resolved Text Evaluation with Masked Diffusion Language Models The paper introduces rate-resolved text evaluation to turn masking rates in diffusion language models into diagnostic scores for text assessment. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Evaluates text models, without multimodal capabilities.
Rate-Resolved Text Evaluation with Masked Diffusion Language Models The paper introduces rate-resolved text evaluation to turn masking rates in diffusion language models into diagnostic scores for text assessment. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Not focused on retrieval-augmented generation architectures.
Rate-Resolved Text Evaluation with Masked Diffusion Language Models The paper introduces rate-resolved text evaluation to turn masking rates in diffusion language models into diagnostic scores for text assessment. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Text evaluation method, not an autonomous agent system.
Rate-Resolved Text Evaluation with Masked Diffusion Language Models The paper introduces rate-resolved text evaluation to turn masking rates in diffusion language models into diagnostic scores for text assessment. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on evaluation metrics, not safety guardrails.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on text embeddings, not multimodal systems.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Not focused on AI safety, hallucination, or guardrails.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Latent space exploratory study, not a benchmark.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Examines literary archetypes, not software code.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Does not explore retrieval-augmented generation architectures.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Embedding geometry study, not about AI agents.
The Mathematical Collective Unconscious: Jungian Archetypes within the Latent Space The paper examines whether large language model embedding spaces naturally form semantic clusters resembling Jungian archetypes using synthetic and human-authored texts. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Not focused on efficient models or compression.
Towards Autopilot Labeling for Short Video Content Governance The paper presents a multi-stage automated labeling framework using multimodal models and agents to annotate short videos for content moderation. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not study model compression or efficient serving.
Towards Autopilot Labeling for Short Video Content Governance The paper presents a multi-stage automated labeling framework using multimodal models and agents to annotate short videos for content moderation. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Presents an automated labeling system, not an evaluation benchmark.
Towards Autopilot Labeling for Short Video Content Governance The paper presents a multi-stage automated labeling framework using multimodal models and agents to annotate short videos for content moderation. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Focuses on video governance, not software engineering.
Towards Autopilot Labeling for Short Video Content Governance The paper presents a multi-stage automated labeling framework using multimodal models and agents to annotate short videos for content moderation. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Not focused on retrieval-augmented generation architectures.
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop This paper synthesizes literature on educational language models to evaluate whether tutoring systems measurably improve student learning gains. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Reviews dialogue tutoring systems, not multimodal models.
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop This paper synthesizes literature on educational language models to evaluate whether tutoring systems measurably improve student learning gains. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Synthesis of educational dialogue systems, not general agents.
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop This paper synthesizes literature on educational language models to evaluate whether tutoring systems measurably improve student learning gains. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Focuses on tutoring dialogues, not code generation.
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop This paper synthesizes literature on educational language models to evaluate whether tutoring systems measurably improve student learning gains. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Does not address retrieval-augmented generation.
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop This paper synthesizes literature on educational language models to evaluate whether tutoring systems measurably improve student learning gains. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on pedagogical efficacy, not deployment safety risks.
Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop This paper synthesizes literature on educational language models to evaluate whether tutoring systems measurably improve student learning gains. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Not focused on model size or inference efficiency.
Generalizable Model Editing Could Be More Than Direct Generalization The authors analyze limitations in direct model editing benchmarks and compare them against observed generalization in practical chat settings. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not address model compression or inference efficiency.
Generalizable Model Editing Could Be More Than Direct Generalization The authors analyze limitations in direct model editing benchmarks and compare them against observed generalization in practical chat settings. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on text LLM editing, not multimodal models.
Generalizable Model Editing Could Be More Than Direct Generalization The authors analyze limitations in direct model editing benchmarks and compare them against observed generalization in practical chat settings. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Studies model editing, not autonomous multi-step agents.
Generalizable Model Editing Could Be More Than Direct Generalization The authors analyze limitations in direct model editing benchmarks and compare them against observed generalization in practical chat settings. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Focuses on weight editing rather than retrieval augmentation.
Generalizable Model Editing Could Be More Than Direct Generalization The authors analyze limitations in direct model editing benchmarks and compare them against observed generalization in practical chat settings. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Not focused on code generation or software engineering.
Preserving Updates in Low-Bit Recurrent State Quantization This paper proposes a low-rank bypass to accumulate small updates and reduce compounding errors in quantized recurrent model states. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Architecture-level state quantization, not about AI agents.
Preserving Updates in Low-Bit Recurrent State Quantization This paper proposes a low-rank bypass to accumulate small updates and reduce compounding errors in quantized recurrent model states. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses memory efficiency rather than safety or alignment.
Preserving Updates in Low-Bit Recurrent State Quantization This paper proposes a low-rank bypass to accumulate small updates and reduce compounding errors in quantized recurrent model states. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Does not propose benchmarks or evaluation methodologies.
Preserving Updates in Low-Bit Recurrent State Quantization This paper proposes a low-rank bypass to accumulate small updates and reduce compounding errors in quantized recurrent model states. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Not focused on external retrieval or grounding.
Preserving Updates in Low-Bit Recurrent State Quantization This paper proposes a low-rank bypass to accumulate small updates and reduce compounding errors in quantized recurrent model states. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Not related to programming assistants or code generation.
Preserving Updates in Low-Bit Recurrent State Quantization This paper proposes a low-rank bypass to accumulate small updates and reduce compounding errors in quantized recurrent model states. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on recurrent model states, not multimodal tasks.
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora TL;QR pairs language-model passage judgments with a symbolic temporal logic engine to track evolving patterns in textual corpora. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Proposes a querying engine, not a model benchmark.
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora TL;QR pairs language-model passage judgments with a symbolic temporal logic engine to track evolving patterns in textual corpora. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Applies to discourse corpora, not code or programming.
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora TL;QR pairs language-model passage judgments with a symbolic temporal logic engine to track evolving patterns in textual corpora. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Declarative query engine, not an autonomous agent framework.
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora TL;QR pairs language-model passage judgments with a symbolic temporal logic engine to track evolving patterns in textual corpora. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on text querying rather than safety or guardrails.
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora TL;QR pairs language-model passage judgments with a symbolic temporal logic engine to track evolving patterns in textual corpora. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Text-only query system, no multimodal data.
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora TL;QR pairs language-model passage judgments with a symbolic temporal logic engine to track evolving patterns in textual corpora. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Not focused on model quantization, distillation, or pruning.
NepPlural: A Human-Anchored Benchmark for Persona Annotation in Nepali Migration Discourse NepPlural provides an annotated benchmark of Nepali discourse to evaluate how reliably language models capture diverse socio-cultural personas. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Does not focus on retrieval-augmented generation.
NepPlural: A Human-Anchored Benchmark for Persona Annotation in Nepali Migration Discourse NepPlural provides an annotated benchmark of Nepali discourse to evaluate how reliably language models capture diverse socio-cultural personas. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Not related to coding assistants or software engineering.
NepPlural: A Human-Anchored Benchmark for Persona Annotation in Nepali Migration Discourse NepPlural provides an annotated benchmark of Nepali discourse to evaluate how reliably language models capture diverse socio-cultural personas. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not explore model compression or efficiency techniques.
NepPlural: A Human-Anchored Benchmark for Persona Annotation in Nepali Migration Discourse NepPlural provides an annotated benchmark of Nepali discourse to evaluate how reliably language models capture diverse socio-cultural personas. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Benchmark for persona annotation, not agent systems.
NepPlural: A Human-Anchored Benchmark for Persona Annotation in Nepali Migration Discourse NepPlural provides an annotated benchmark of Nepali discourse to evaluate how reliably language models capture diverse socio-cultural personas. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Examines text comments only, without multimodal components.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not study compression or efficient model serving.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Not related to retrieval-augmented systems.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	AI agents via arxiv · 15 Oct, 06:18	Not relevant Studies sentiment classification, not agentic planning.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	LLMs for code via arxiv · 15 Oct, 06:18	Not relevant Focuses on natural language sentiment, not code generation.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on classification accuracy across domains, not safety.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals strictly with text datasets.
Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi This paper studies multi-domain training setups to improve zero-shot sentiment classification transfer across unseen domains in Marathi. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Empirical study on domain transfer, not benchmark design.
Robust Marathi Sentiment Analysis using Domain-Adaptive Pre-training and Data Augmentation Approaches The authors evaluate domain-adaptive pretraining and back-translation data augmentation to improve sentiment classification in Marathi. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Applies standard training techniques, no novel evaluation paradigm.
Robust Marathi Sentiment Analysis using Domain-Adaptive Pre-training and Data Augmentation Approaches The authors evaluate domain-adaptive pretraining and back-translation data augmentation to improve sentiment classification in Marathi. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant Standard classification task, not retrieval-augmented generation.

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