Every paper checked — nothing hidden

All papers

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
ELECT: Settling Identity Before Rendering for Scalable Story Visualization The paper proposes a training-free method establishing entity identity before final rendering to maintain visual consistency across long storyboards. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Concerns story visualization efficiency, not AI safety.
ELECT: Settling Identity Before Rendering for Scalable Story Visualization The paper proposes a training-free method establishing entity identity before final rendering to maintain visual consistency across long storyboards. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant Generates visual story frames, not industrial visual inspection.
Self-Representation Alignment in Diffusion Models for Video Background Music Generation The paper introduces an internal feature alignment loss for diffusion models to improve background music generation from video inputs. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Deals with video-to-music diffusion models, not autonomous agents.
Self-Representation Alignment in Diffusion Models for Video Background Music Generation The paper introduces an internal feature alignment loss for diffusion models to improve background music generation from video inputs. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Addresses generative media alignment, not AI deployment safety.
Self-Representation Alignment in Diffusion Models for Video Background Music Generation The paper introduces an internal feature alignment loss for diffusion models to improve background music generation from video inputs. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Presents a generative audio-visual architecture, not an evaluation benchmark.
Inverse Garment Design with Visual Agents The paper introduces an agentic system that reconstructs multi-layer 3D garment sewing patterns from a single image using simulation feedback. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes an inverse design framework, not an evaluation benchmark.
Inverse Garment Design with Visual Agents The paper introduces an agentic system that reconstructs multi-layer 3D garment sewing patterns from a single image using simulation feedback. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on garment modeling, not AI safety or guardrails.
CondMSP: Condition-Informed and Resource-Aware Inorganic Materials Synthesis Planning The paper presents an inorganic materials synthesis framework that incorporates condition prediction as context to guide reaction route planning. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Addresses materials science route planning, not LLM evaluation.
CondMSP: Condition-Informed and Resource-Aware Inorganic Materials Synthesis Planning The paper presents an inorganic materials synthesis framework that incorporates condition prediction as context to guide reaction route planning. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Domain-specific materials synthesis planning, not general LLM agents.
CondMSP: Condition-Informed and Resource-Aware Inorganic Materials Synthesis Planning The paper presents an inorganic materials synthesis framework that incorporates condition prediction as context to guide reaction route planning. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Covers materials discovery algorithms, not AI safety risks.
From Stages to States: Unified Iterative Reasoning for MLLMs The paper proposes an iterative reasoning framework that models intermediate multimodal reasoning steps as dynamic state transitions. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Presents a multimodal reasoning technique, not an evaluation framework.
From Stages to States: Unified Iterative Reasoning for MLLMs The paper proposes an iterative reasoning framework that models intermediate multimodal reasoning steps as dynamic state transitions. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on multimodal reasoning performance, not deployment safety.
From Stages to States: Unified Iterative Reasoning for MLLMs The paper proposes an iterative reasoning framework that models intermediate multimodal reasoning steps as dynamic state transitions. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Addresses internal reasoning chains, not tool-using or autonomous agents.
Big-Big-SycoBench: A Benchmark to Detect Sycophancy Through Model Responses to Valid vs. Invalid Arguments The paper introduces a benchmark measuring whether language models resist sycophancy when presented with invalid user arguments versus valid critiques. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Measures model sycophancy, not multi-step planning or tool use.
Recall What Is Missing: Composing Evidence from Long-Term Agent Memory The paper presents a training-free memory selection method that progressively composes non-redundant evidence sets for long-term agents. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on memory retrieval efficiency, not deployment safety.
Recall What Is Missing: Composing Evidence from Long-Term Agent Memory The paper presents a training-free memory selection method that progressively composes non-redundant evidence sets for long-term agents. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Evaluates a memory mechanism, not proposing general LLM benchmarks.
Dynamic Conflict Clustering with Lightweight Learning and Strategic Repair for Distributed Constraint Satisfaction The paper introduces a conflict-clustering solver with lightweight learning to coordinate distributed agents solving constraint satisfaction problems. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on distributed constraint solving algorithms, not safety.
Dynamic Conflict Clustering with Lightweight Learning and Strategic Repair for Distributed Constraint Satisfaction The paper introduces a conflict-clustering solver with lightweight learning to coordinate distributed agents solving constraint satisfaction problems. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Presents a DCSP solver, not an LLM evaluation benchmark.
Knowledge Interaction in Hypernetwork-based Continual Learning: Conflict and Composition The paper examines how hypernetwork adapters resolve knowledge conflicts and compose information during continual learning in language models. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Examines continual learning and hypernetworks, not LLM agents.
Knowledge Interaction in Hypernetwork-based Continual Learning: Conflict and Composition The paper examines how hypernetwork adapters resolve knowledge conflicts and compose information during continual learning in language models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Analyzes internal knowledge interactions, not evaluation benchmarking.
Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning The paper presents a dataset and framework mapping sketches and text to executable parametric computer-aided design code. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:17	Not relevant Focuses on CAD generation from sketches, not industrial defect detection.
Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning The paper presents a dataset and framework mapping sketches and text to executable parametric computer-aided design code. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Introduces a CAD dataset/method, not an LLM benchmark.
Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning The paper presents a dataset and framework mapping sketches and text to executable parametric computer-aided design code. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Concerns CAD code generation, not AI deployment safety.
Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning The paper presents a dataset and framework mapping sketches and text to executable parametric computer-aided design code. Peer-reviewed	AI agents via arxiv · 15 Oct, 06:17	Not relevant Focuses on generative CAD modeling, not multi-step LLM agents.
Radioactive Feedback: Tracing Models Trained by Label-Only LLM Supervision The paper proposes an evaluation technique that embeds behavioral traces into score-only feedback to trace distilled student models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Studies distillation provenance, not general evaluation methodologies.
Radioactive Feedback: Tracing Models Trained by Label-Only LLM Supervision The paper proposes an evaluation technique that embeds behavioral traces into score-only feedback to trace distilled student models. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Focuses on distillation watermarking, not agent tool use or planning.
FARL: A Fully Automated Pipeline of RL Interface and Solver Design The paper presents an automated framework that jointly designs reinforcement learning observation spaces, reward programs, algorithms, and training configurations. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes an automated RL search pipeline, not a benchmark.
FARL: A Fully Automated Pipeline of RL Interface and Solver Design The paper presents an automated framework that jointly designs reinforcement learning observation spaces, reward programs, algorithms, and training configurations. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on RL pipeline optimization, not deployment safety.
TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks The paper presents an in-context diffusion model for generating, completing, and synthesizing unseen tabular data records jointly. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Addresses tabular data generation, not AI deployment safety or jailbreaks.
TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks The paper presents an in-context diffusion model for generating, completing, and synthesizing unseen tabular data records jointly. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Covers tabular diffusion models, not LLM-based autonomous agents.
TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks The paper presents an in-context diffusion model for generating, completing, and synthesizing unseen tabular data records jointly. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on in-context diffusion for tables, not model compression.
TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks The paper presents an in-context diffusion model for generating, completing, and synthesizing unseen tabular data records jointly. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes a tabular generative model, not an evaluation benchmark.
RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification The paper introduces a weakly supervised learning framework and dataset for identifying acoustic evidence in respiratory sound classification. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Medical sound dataset study, not general LLM evaluation.
RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification The paper introduces a weakly supervised learning framework and dataset for identifying acoustic evidence in respiratory sound classification. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Focuses on sound classification, not LLM planning or agents.
RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification The paper introduces a weakly supervised learning framework and dataset for identifying acoustic evidence in respiratory sound classification. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Deals with weakly supervised acoustic classification, not model efficiency.
RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification The paper introduces a weakly supervised learning framework and dataset for identifying acoustic evidence in respiratory sound classification. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Addresses medical diagnosis classification, not deployment safety or guardrails.
bharatSetu: a 1M x 22 bridge for indic translation The paper introduces a synthetic parallel translation dataset covering 22 scheduled Indic languages aligned via English pivot sentences. Preprint	LLMs for code via arxiv · 15 Oct, 06:17	Not relevant Deals with natural language translation, not programming or code generation.
bharatSetu: a 1M x 22 bridge for indic translation The paper introduces a synthetic parallel translation dataset covering 22 scheduled Indic languages aligned via English pivot sentences. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:17	Not relevant Focuses on parallel translation corpora, not retrieval-augmented generation.
bharatSetu: a 1M x 22 bridge for indic translation The paper introduces a synthetic parallel translation dataset covering 22 scheduled Indic languages aligned via English pivot sentences. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Introduces a machine translation corpus, not multi-step agents.
bharatSetu: a 1M x 22 bridge for indic translation The paper introduces a synthetic parallel translation dataset covering 22 scheduled Indic languages aligned via English pivot sentences. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Concerns translation dataset curation, not AI safety or alignment.
bharatSetu: a 1M x 22 bridge for indic translation The paper introduces a synthetic parallel translation dataset covering 22 scheduled Indic languages aligned via English pivot sentences. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Presents a dataset and translation pairs, not model compression.
bharatSetu: a 1M x 22 bridge for indic translation The paper introduces a synthetic parallel translation dataset covering 22 scheduled Indic languages aligned via English pivot sentences. Preprint	Multimodal models via arxiv · 15 Oct, 06:17	Not relevant Focuses purely on text translation, not multimodal text-and-image data.
SpecForge: Recursive Self-Improvement for Coding Agents via Behavioral Specifications The paper presents a self-improvement method where coding agents refine natural-language behavioral specifications using execution-verified tests. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on code specification refinement, not AI safety or security.
SpecForge: Recursive Self-Improvement for Coding Agents via Behavioral Specifications The paper presents a self-improvement method where coding agents refine natural-language behavioral specifications using execution-verified tests. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Proposes an agent improvement framework rather than a testing benchmark.
What DNA Foundation Models Learn Beyond Sequence Composition The paper evaluates whether genomic foundation models offer predictive value over simple sequence frequency baselines across classification benchmarks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Studies biological sequence representations, not LLM evaluation methods.
What DNA Foundation Models Learn Beyond Sequence Composition The paper evaluates whether genomic foundation models offer predictive value over simple sequence frequency baselines across classification benchmarks. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Evaluates DNA foundation models, not multi-step autonomous agents.
What DNA Foundation Models Learn Beyond Sequence Composition The paper evaluates whether genomic foundation models offer predictive value over simple sequence frequency baselines across classification benchmarks. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Compares genomic representation features, not model compression or efficiency.
What DNA Foundation Models Learn Beyond Sequence Composition The paper evaluates whether genomic foundation models offer predictive value over simple sequence frequency baselines across classification benchmarks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Analyzes genomic feature representations, not deployment safety or guardrails.
History Replays Itself: Unleashing Long-Context Capability in Linear Attention The paper proposes a training-free episodic memory mechanism that extends linear attention language models to long-context tasks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Focuses on long-context modeling capacity, not AI safety or guardrails.
History Replays Itself: Unleashing Long-Context Capability in Linear Attention The paper proposes a training-free episodic memory mechanism that extends linear attention language models to long-context tasks. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Proposes an attention memory mechanism, not multi-step LLM agents.
History Replays Itself: Unleashing Long-Context Capability in Linear Attention The paper proposes a training-free episodic memory mechanism that extends linear attention language models to long-context tasks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Introduces an architectural memory module rather than an evaluation benchmark.
Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework The paper integrates quality-diversity optimization with diffusion models to generate diverse sets of high-performing outputs. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Introduces an optimization algorithm for diffusion, not LLM evaluation.
Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework The paper integrates quality-diversity optimization with diffusion models to generate diverse sets of high-performing outputs. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on output diversity in diffusion models, not efficient inference.
Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework The paper integrates quality-diversity optimization with diffusion models to generate diverse sets of high-performing outputs. Preprint	AI agents via arxiv · 15 Oct, 06:17	Not relevant Studies diffusion sampling optimization, not multi-step language agents.
Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework The paper integrates quality-diversity optimization with diffusion models to generate diverse sets of high-performing outputs. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Explores sample diversity in diffusion, not deployment safety or robustness.
SkillMarker: A KGW-Based Watermarking Method for Agent Skill Ownership Verification The paper introduces a watermarking method to verify ownership and trace unauthorized copying of agent skill instructions. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:17	Not relevant Focuses on watermarking mechanisms rather than evaluation benchmark methodology.
Visible but Not Avoided: State-Dependent Re-Proposal of Rejected Candidates in Catalog-Based LLM Optimization Loops The paper demonstrates that language model optimizers frequently re-propose previously rejected candidates during search trajectories. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Studies optimization loop efficiency, not AI safety or guardrails.
Google Earth AI Geospatial Reasoning Agent: Capabilities and a Systematic Evaluation The paper presents Google Earth AI's geospatial reasoning agent along with evaluation benchmarks for complex multi-step geospatial workflows. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Presents geospatial agent workflows, not AI safety or alignment risks.
Hyperbolic Time Series Forecasting with Learnable Decomposition and Manifold Dynamics The paper proposes a hyperbolic time series forecasting framework that maps multiscale frequency hierarchies onto the Poincaré ball. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:17	Not relevant Deals with time series forecasting accuracy, not AI deployment safety.
Hyperbolic Time Series Forecasting with Learnable Decomposition and Manifold Dynamics The paper proposes a hyperbolic time series forecasting framework that maps multiscale frequency hierarchies onto the Poincaré ball. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Proposes a geometric representation framework, not model compression or efficiency.

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