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

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Ranking and Partitioning of Attention Heads for Sparse and Continual Reinforcement Learning Fine-tuning
The paper studies ranking and partitioning attention heads by gradient norm for sparse and continual reinforcement learning fine-tuning.
Ranked #446Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:17
On-topic
Proposes sparse attention-head tuning to reduce training and adaptation overhead across tasks.
AgentEval: Evidence-Bounded Assessment of Stateful Agents
Presents an evaluation system that tracks state and evidence to ensure autonomous agents fulfill obligations across long-horizon executions.
Ranked #446New testPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Addresses obligation satisfaction and evidence tracking for stateful tool-using agents.
FRACTION: Fraud Explanation Generation via Agentic Graph Context Navigation
This paper presents an agentic framework and an evaluation rubric for generating explanations of risk labels in graph fraud detection.
Ranked #446New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Introduces a validated evaluation rubric and protocol for assessing LLM-generated fraud explanations.
FrameLite: Decision-Oriented Aesthetic Cropping with a Compact Vision-Language Model
Proposes a lightweight aesthetic cropping model built on a small vision-language model using multi-stage candidate optimization.
Ranked #446Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Uses a compact vision-language model for image composition and cropping.
The belief-action gap in language model agents
The authors examine why language model agents fail by analyzing discrepancies between internal representations of state values and actual action choices.
Ranked #446New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Analyzes internal causes of failure and unreliability in language model agent actions.
Data Strategies for Large Language Models: A Unified Perspective on the Training Lifecycle
Reviews and formalizes data selection, weighting, and scheduling policies across the pretraining and post-training lifecycle of language models.
Ranked #447Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:17
On-topic
Analyzes compute-budget allocation and training data efficiency across model lifecycles.
MemScope: Evolving Agent Memory Architectures through Localized Code Repair
Introduces a localized code repair framework that evolves language model memory architectures using fine-grained execution feedback.
Ranked #447New way to see a problemPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Proposes a framework for self-evolving agent memory architectures via localized code repair during task execution.
Multimodal Fusion of RGB and Complementary Modalities for Semantic Segmentation
This paper proposes a bidirectional polarity-aware cross-modality fusion module to improve multimodal semantic segmentation across diverse complementary sensor streams.
Ranked #447Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Develops a cross-modality fusion framework for combining RGB with complementary modalities like LiDAR, depth, and thermal.
How to Build a Benchmark That Actually Measures Taste
This paper introduces a pairwise evaluation benchmark and protocol designed to measure subjective aesthetic taste while controlling for shortcut artifacts.
Ranked #447New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:17
On-topic
Introduces a new benchmark and evaluates biases and construction artifacts in model evaluation.
Learning to Detect Shifts in Unstructured Data Streams via Monitoring-by-Betting
The paper develops a sequential betting approach to reliably detect data distribution shifts in unstructured text and image streams over time.
Ranked #447New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Provides monitoring methods to detect distribution shifts in generative AI data streams.
BitSparse: Compact Activation Storage for ReLU Feed-Forward Networks
Presents a GPU format that losslessly compresses sparse activations to reduce memory usage during neural network training.
Ranked #448Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Introduces a lossless activation compression format to reduce GPU memory during LLM training.
RAC: A Relational Agent Contract for Constraint-Governed Engineering Tasks
The paper introduces an action and feedback contract separating agent decisions from deterministic tool execution for constraint-governed engineering tasks.
Ranked #448New way to see a problemPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Proposes an action-feedback contract enabling agents to solve constraint-governed engineering tasks.
IND-Eval: Aligning Evaluation and Simulation for Industrial Time Series Foundation Models
The paper introduces an industrial time-series forecasting benchmark to evaluate foundation models on multi-rate and multivariate data.
Ranked #448New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Introduces a public evaluation benchmark for industrial time series models.
WIRE: Weight Space Implicit Representation Encoding of Frozen Video LLMs
WIRE reduces video LLM inference costs by moving video computations from input tokens into temporary low-rank weight updates.
Ranked #448Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Optimizes video language models by encoding visual representation into model weights.
MAS-Gate: Unlocking Multi-Agent System Lifecycle via Node-Centric Quantification
The paper presents a unified node-centric framework to quantify and manage multi-agent system lifecycles across design, runtime, and post-hoc attribution.
Ranked #448New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Provides runtime monitoring and attribution mechanisms to stabilize multi-agent execution.
Query-Efficient Rejection Sampling for Parallel Masked Diffusion
Proposes a single-increment rejection sampling algorithm to correct token correlation bias efficiently in parallel masked diffusion.
Ranked #449Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Improves parallel masked diffusion decoding efficiency via single-query rejection sampling.
SkillNEO: Non-Elitist Evolutionary Optimization of Agent Skills
The paper proposes a non-elitist evolutionary optimization framework that retains and iteratively refines low-reward agent skills using execution feedback.
Ranked #449Surprising resultPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Optimizes agent skill banks via evolutionary refinement to improve task completion.
AI-Assisted Tumor-Growth Law Discovery from Sparse Data: Refitting and LLM-Based Ranking
The paper evaluates symbolic regression, refitting techniques, and language model rankings for inferring tumor-growth laws from sparse observation data.
Ranked #449Surprising resultPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Evaluates LLM reasoning and ranking capabilities for scientific equation discovery.
Learning Multimodal Sensor Fusion with JEPA Representations for Breathing Activity and Pose Recognition
The paper explores transferring frozen video representations across heterogeneous sensor subsets to classify breathing activity and pose.
Ranked #449Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:17
On-topic
Studies multimodal fusion across video, depth, and radar sensor inputs.
Verifier-Harness Co-Evolution for Training-Free Self-Improvement on Open-Ended Tasks
The paper proposes a training-free framework that co-evolves an executable verifier program and harness state to self-improve agents on open-ended tasks.
Ranked #449Surprising resultPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Improves response reliability and verification on open-ended deployment tasks.
LCT: Losslessly Compressed Tensors with GPU friendly execution for Training
Provides a GPU-accelerated Huffman compression framework for tensors to lower memory overhead during model training.
Ranked #450Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Presents lossless GPU tensor compression to reduce memory footprint during model training.
Amortizing Sequential Experimental Design in Reasoning LLMs
The paper trains reasoning models to perform sequential experimental design by optimizing information-gain rewards during action selection.
Ranked #450New way to see a problemPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Trains reasoning LLMs to adaptively acquire information in multi-step tasks.
DDVR-Net: Degradation-Aware Decoupling and Visibility-Guided Restoration for Historical Document Recognition
DDVR-Net decouples glyph structures from physical damage and uses visibility-guided restoration for historical document OCR.
Ranked #450Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Presents a framework combining visual degradation restoration with language modeling for document understanding.
Improving the Evaluation of Biomedical Question Answering with Few Human Preference Signals
This paper uses limited human preference signals to calibrate automated evaluation metrics for biomedical retrieval-augmented question answering.
Ranked #450New way to see a problemPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Proposes calibrating automated evaluation metrics with human preferences to evaluate QA systems.
From Token Correction to Claim Admission: Training-Free Hallucination Mitigation for Large Vision-Language Models
Proposes a training-free framework that mitigates vision-language model hallucinations by admitting claims only when supported relative to a visual-null input.
Ranked #450New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Introduces a training-free framework to reduce object hallucination in vision-language models.
ETH: Data-Balanced Heterogeneous Pipeline Parallelism for Training Large Models
This paper presents a pipeline parallelism training system that balances data workloads across heterogeneous hardware while reducing communication overhead.
Ranked #451Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Proposes pipeline parallelism to improve memory and compute efficiency for training large models.
ARIA: Runtime Inspection and Amendment for Multi-Agent Systems
The paper presents a framework and dataset for learning to detect and repair errors during multi-agent system execution.
Ranked #451New way to see a problemPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Proposes a runtime inspection and amendment framework to repair multi-agent system execution errors.
XForecast: The KDD 2026 Finance Day Challenge on News-Grounded Financial Forecasting
This paper introduces a financial forecasting benchmark and competition that evaluates four-week stock movement predictions using both prices and news.
Ranked #451New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Introduces a financial forecasting benchmark and metric evaluating multimodal time-series and news text integration.
Geometry-Guided Semantic Reconstruction for 3D Instance Segmentation
Introduces masked semantic reconstruction and geometry modulation to better align lifted 2D semantic priors with 3D instance representations.
Ranked #451Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Transfers and aligns 2D semantic priors into 3D geometric representations for scene understanding.
Can Agents Truly Forget? Explore Machine Unlearning for LLM Agents
Formulates machine unlearning for LLM agents across parametric memory, external persistent storage, and tool-accessible environments.
Ranked #451New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Focuses on preventing LLM agents from leaking sensitive enterprise or user data.
Learning Lean Feedback for Efficient Proof-Candidate Evaluation on GPUs
This paper trains GPU-based neural evaluators to predict Lean 4 compiler verdicts and feedback, accelerating proof-candidate filtering.
Ranked #452Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Accelerates formal verification by using lightweight neural surrogates to speed up theorem prover evaluation.
Stop Training Against Soft Users: Mentalized Adversarial Self-Play for Proactive Dialogue
The paper introduces an adversarial self-play framework modeling user mental states to improve proactive dialogue agent planning.
Ranked #452New way to see a problemPreprint6/10 suggested
AI agents
via arxiv · 17 Oct, 06:17
On-topic
Focuses on proactive dialogue agents planning actions against evolving user states.
PATTERN Can Be Solved from Memory: Generator-Aware Baselines for Synthetic Node Classification
Shows the PATTERN graph benchmark can be solved by memorization because pattern subgraphs are reused across splits.
Ranked #452Surprising resultPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Exposes fundamental data leakage and design flaws in synthetic graph benchmarks.
PIGEONS: Incremental Long-Video Captioning with Persistent Identity Gallery and Evolving Overarching Narrative Summary
Develops an incremental long-video captioning method using a persistent identity gallery and evolving narrative summary.
Ranked #452Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Develops a multimodal video captioning framework using identity galleries and narrative summaries.
Transparent Information Flow Modeling for Role-Aware AI Act Assessment
The paper applies an information-flow modeling methodology to assess public-sector AI recruitment tools under European Union AI Act requirements.
Ranked #452New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Addresses AI Act compliance, governance, and accountability in high-risk deployments.
Compiling Multi-Threshold Operators for Quantized Non-Monotonic and Fine-Granular Activations in Custom-Tailored DNN Accelerators
The paper proposes an ONNX compiler method to map quantized non-monotonic and fine-granular activations into multi-threshold operators for hardware accelerators.
Ranked #453Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Compiles multi-threshold operators to enable hardware-efficient quantized activation functions.
Rethinking Opinion Measurement Interfaces for Human-in-the-Loop Optimization
This paper evaluates human opinion measurement interfaces and recommends listwise preference collection for human-in-the-loop optimization.
Ranked #453New way to see a problemPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:18
On-topic
Investigates user interface designs and human evaluation protocols for assessing model outputs.
EviStress: Evidence Stress Learning for Generalizable Face Forgery Detection with Textual Explanations
The paper introduces a framework combining targeted patch perturbation with textual explanations to improve face forgery detection generalization.
Ranked #453Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Proposes a framework for face forgery detection with multimodal textual explanations.
claimcheck: Measuring and Improving Specification Faithfulness
The paper presents a benchmark to evaluate whether formal specifications generated by language models accurately reflect natural-language requirements.
Ranked #453New testPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Focuses on preventing unfaithful specifications in deployed formal verification systems.
Urbex: Agentic Spatial Grounding for City-Scale 3D Scenes
The authors present an active spatial search framework enabling vision-language agents to ground 3D objects in city-scale environments via interactive tool use.
Ranked #453New way to see a problemPreprint5/10 suggested
AI agents
via arxiv · 15 Oct, 06:17
On-topic
Designs an active spatial search agent using interactive tools in 3D scenes.
Sparse Federated Echo State Networks for Time-Series Classification via Smooth-L1 Regularization
The paper presents a sparse federated Echo State Network using smooth L1 regularization for efficient edge time-series classification.
Ranked #454Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Presents a sparse regularized network to reduce stored model size and inference cost.
One-Step Prediction Fidelity Is a Poor Proxy for Planning Performance in JEPA World Models
The paper shows that one-step prediction accuracy in joint-embedding world models is an unreliable indicator of downstream planning performance.
Ranked #454Surprising resultPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 15:06
On-topic
Evaluates whether one-step prediction metrics reliably reflect planning performance in world models.
ViewStruct: View-Grounded Articulation and Connectivity Inference
The paper proposes a vision-language framework to predict rigid-body connectivity and articulation parameters of objects from single views.
Ranked #454Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Adapts vision-language models to perform multimodal reasoning over visual scenes and object connectivity.
Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents
Proposes a decentralized identity framework using self-sovereign identity principles to establish verification and accountability for autonomous agents.
Ranked #454New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Establishes cryptographic identity and governance for safe real-world agent deployments.
Can AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition
Introduces AAArena, a benchmark evaluating how AI agents revise executable code policies across 12 adversarial games under fixed budgets.
Ranked #454New testPreprint5/10 suggested
AI agents
via arxiv · 12 Oct, 16:28
On-topic
Examines LLM agents acting to adapt game policies and code over multi-step iterations.
ShiftQAT: Quantization-Aware Training for the Numerical Contract of a Fixed-Function Edge CNN Accelerator
The paper details a quantization-aware training workflow that trains neural networks to match the exact hardware constraints of edge accelerators.
Ranked #455Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Develops quantization-aware training specifically to satisfy constraints of edge accelerators.
PathPilot: An Adaptive Question-Conditioned Multi-Magnification Navigation Agent for Whole-Slide Image Analysis
The paper proposes an adaptive whole-slide image navigation agent that models cross-magnification localization for pathology diagnosis.
Ranked #455Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Presents an adaptive question-conditioned multimodal navigation agent for complex medical image analysis.
Gradient Routing Localizes and Removes Unintended Behaviors in RL
Routes gradients from imperfect monitor flags into sacrificial parameters to mitigate reward hacking during reinforcement learning.
Ranked #455New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Presents a method to mitigate reward hacking and unintended behavior in reinforcement learning.
APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation
This paper introduces an agentic post-training framework that coordinates multiple agents to evaluate and adaptively train text-to-image models.
Ranked #455New way to see a problemPreprint5/10 suggested
AI agents
via arxiv · 15 Oct, 06:17
On-topic
Uses coordinating multi-agent systems to automate evaluation and post-training data generation.
LIBERO-RIG: A Hardware-Setup Robustness Benchmark for Vision-Language-Action Models
The paper introduces a benchmark to measure vision-language-action model robustness against hardware, optical, and physical robot setup variations.
Ranked #455New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:17
On-topic
Introduces LIBERO-RIG, a standardized benchmark evaluating policy robustness under hardware setup changes.
Recursive Offline Distillation via Entropy Gain Sampling and Answer Mixing
The paper presents an offline distillation method combining entropy-difference sampling and answer mixing to transfer reasoning abilities into smaller language models.
Ranked #456Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Proposes an offline distillation method to transfer reasoning capabilities into small models.
Revisiting Natural Language Prompts from Large Language Models for Open-Vocabulary Video Recognition
The paper presents a framework exploring category, video, and frame prompts to enhance vision-language models for open-vocabulary video recognition.
Ranked #456Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Improves vision-text alignment in multimodal vision-language models for video recognition.
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.
Ranked #456New way to see a problemPreprint5/10 suggested
AI agents
via arxiv · 15 Oct, 06:17
On-topic
Addresses ownership verification and leakage prevention for reusable agent skill procedures.
Answer It or Not? Towards Prompt-Adapted Adversarial Images on Vision Language Models
Generates prompt-adapted adversarial images that block unauthorized visual questions on vision-language models while still answering legitimate prompts correctly.
Ranked #456New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Investigates adversarial attacks and privacy protections for deployed vision-language models.
GIFT-Eval-CTX: A Benchmark For Contextual Forecasting Model Evaluation
This paper introduces a benchmark to evaluate whether forecasting models can incorporate forward-looking contextual information into accurate time-series predictions.
Ranked #456New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:17
On-topic
Presents GIFT-Eval-CTX, a dedicated benchmark for evaluating contextual time-series forecasting across models.
Fault Detection and Bit-Error Rate Diagnostics in Optical Wireless Links Using Edge-AI
The authors implement an on-device machine learning diagnostic engine on a microcontroller for optical wireless communication links.
Ranked #457Preprint0/10 suggested
Small and efficient models
via arxiv · 17 Oct, 06:18
On-topic
Demonstrates an INT8 quantized TinyML neural network deployed on a microcontroller for edge processing.
Code-Interactive Visual Reasoning for Financial Candlestick Understanding
The paper introduces a model and dataset for financial candlestick reasoning by generating and executing code to gather visual evidence.
Ranked #457Preprint0/10 suggested
Multimodal models
via arxiv · 15 Oct, 06:18
On-topic
Develops vision-language reasoning combining document understanding of financial charts with code execution.
Does the Explanation Drift Before the Guarantee? Label-Free Early Warning on Evolving Graphs
Monitors model explanation drift on evolving graphs to provide early warnings before predictive uncertainty guarantees fail.
Ranked #457New way to see a problemPreprint6/10 suggested
AI safety and reliability in deployment
via arxiv · 15 Oct, 06:17
On-topic
Provides early-warning attribution drift monitoring to maintain reliability and conformal coverage in deployment.
Monitoring latent reasoning in looped language models
This paper presents an interpretability protocol to monitor latent reasoning dynamics and stability across multiple looped language model families.
Ranked #457New testPreprint5/10 suggested
LLM evaluation and benchmarks
via arxiv · 15 Oct, 06:17
On-topic
Introduces an interpretability evaluation protocol to assess looped language models.
Mental-Models for Multi-Agent Systems
Equips multi-agent systems with latent mental models to infer counterpart beliefs and intentions for better decision-making under partial observability.
Ranked #457New way to see a problemPreprint5/10 suggested
AI agents
via arxiv · 12 Oct, 16:29
On-topic
Proposes latent partner-state mental models for multi-agent reasoning and decision-making.
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