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Filtered Reasoning Score: Evaluating Reasoning Quality on a Model's Most-Confident Traces

arXiv:2604.11996v1 Announce Type: cross Abstract: Should we trust Large Language Models (LLMs) with high accuracy? LLMs achieve high accuracy on reasoning benchmarks, but correctness alone does not re

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Human DGX agent

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Fine-tuning Factor Augmented Neural Lasso for Heterogeneous Environments

DGX agent

arXiv:2604.12288v1 Announce Type: cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its methodology and theoretical properties in high-dimensional

model-releasesarxiv-cs-lg

15 Apr 2026

Hardware

Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data

arXiv:2503.10676v2 Announce Type: replace-cross Abstract: We study the efficacy of fine-tuning Large Language Models (LLMs) for the specific task of report (government archives, news, intelligence rep

hardwarearxiv-cs-ai

FlowBoost Reveals Phase Transitions and Spectral Structure in Finite Free Information Inequalities

model-releasesarxiv-cs-lg

arXiv:2604.11922v1 Announce Type: cross Abstract: Using FlowBoost, a closed-loop deep generative optimization framework for extremal structure discovery, we investigate ell^p-generalizations of the fi

FlowPlan-G2P: A Structured Generation Framework for Transforming Scientific Papers into Patent Descriptions

arXiv:2601.02589v2 Announce Type: replace-cross Abstract: Over 3.5 million patents are filed annually, with drafting patent descriptions requiring deep technical and legal expertise. Transforming scie

applicationsarxiv-cs-ai

Local Ai

FMASH: Advancing Traditional Chinese Medicine Formula Recommendation with Efficient Fusion of Multiscale Associations of Symptoms and Herbs

arXiv:2503.05167v3 Announce Type: replace Abstract: Traditional Chinese medicine (TCM) exhibits remarkable therapeutic efficacy in healthcare through patient-specific formulas. However, current AI-bas

local-aiarxiv-cs-lg

Forecasting the Past: Gradient-Based Distribution Shift Detection in Trajectory Prediction

arXiv:2604.12425v1 Announce Type: new Abstract: Trajectory prediction models often fail in real-world automated driving due to distributional shifts between training and test conditions. Such distribu

applicationsarxiv-cs-lg

Fragile Preferences: A Deep Dive Into Order Effects in Large Language Models

arXiv:2506.14092v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in decision-support systems for high-stakes domains such as hiring and university admissions,

Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images

arXiv:2604.12781v1 Announce Type: new Abstract: Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. A

safetyarxiv-cs-cv

Free Random Projection for In-Context Reinforcement Learning

arXiv:2504.06983v3 Announce Type: replace Abstract: Hierarchical inductive biases are hypothesized to promote generalizable policies in reinforcement learning, as demonstrated by explicit hyperbolic l

researcharxiv-cs-lg

Frequency-aware Decomposition Learning for Sensorless Wrench Forecasting on a Vibration-rich Hydraulic Manipulator

arXiv:2604.12905v1 Announce Type: cross Abstract: Force and torque (F/T) sensing is critical for robot-environment interaction, but physical F/T sensors impose constraints in size, cost, and fragility

applicationsarxiv-cs-lg

From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception

arXiv:2604.12508v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding, they frequently falter in fine

researcharxiv-cs-cv

From edges to meaning: Semantic line sketches as a cognitive scaffold for ancient pictograph invention

arXiv:2604.12865v1 Announce Type: new Abstract: Humans readily recognize objects from sparse line drawings, a capacity that appears early in development and persists across cultures, suggesting neural

From Imitation to Discrimination: Progressive Curriculum Learning for Robust Web Navigation

model-releasesarxiv-cs-cl

arXiv:2604.12666v1 Announce Type: cross Abstract: Text-based web agents offer computational efficiency for autonomous web navigation, yet developing robust agents remains challenging due to the noisy

From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution

arXiv:2604.12474v1 Announce Type: cross Abstract: In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission. Such problems are inherently mixed discrete-continuou

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

From Plan to Action: How Well Do Agents Follow the Plan?

arXiv:2604.12147v1 Announce Type: cross Abstract: Agents aspire to eliminate the need for task-specific prompt crafting through autonomous reason-act-observe loops. Still, they are commonly instructed

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization

arXiv:2604.12290v1 Announce Type: new Abstract: Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often negl

FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation

arXiv:2604.12344v1 Announce Type: cross Abstract: The exponential growth of data from modern radio telescopes presents a significant challenge to traditional single-pulse search algorithms, which are

Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference

arXiv:2604.12168v1 Announce Type: cross Abstract: The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transport

Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration

arXiv:2604.12351v1 Announce Type: new Abstract: Automated diagnosis based on color fundus photography is essential for large-scale glaucoma screening. However, existing deep learning models are typica

Agents

GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

arXiv:2604.12285v1 Announce Type: new Abstract: To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining

agentsarxiv-cs-ai

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix

arXiv:2510.06685v2 Announce Type: replace-cross Abstract: Self-attention layers have become fundamental building blocks of modern deep neural networks, yet their theoretical understanding remains limi

researcharxiv-cs-lg

GCA Framework: A Gulf-Grounded Dataset and Agentic Pipeline for Climate Decision Support

arXiv:2604.12306v1 Announce Type: cross Abstract: Climate decision-making in the Gulf increasingly demands systems that can translate heterogeneous scientific and policy evidence into actionable guida

GeM-EA: A Generative and Meta-learning Enhanced Evolutionary Algorithm for Streaming Data-Driven Optimization

arXiv:2604.12336v1 Announce Type: cross Abstract: Streaming Data-Driven Optimization (SDDO) problems arise in many applications where data arrive continuously and the optimization environment evolves

Tutorials

Generating Effective CoT Traces for Mitigating Causal Hallucination

arXiv:2604.12748v1 Announce Type: new Abstract: Although large language models (LLMs) excel in complex reasoning tasks, they suffer from severe causal hallucination in event causality identification (

tutorialsarxiv-cs-cl

Generative Anonymization in Event Streams

arXiv:2604.12803v1 Announce Type: new Abstract: Neuromorphic vision sensors offer low latency and high dynamic range, but their deployment in public spaces raises severe data protection concerns. Rece

Generative Modeling Enables Molecular Structure Retrieval from Coulomb Explosion Imaging

arXiv:2511.00179v2 Announce Type: replace-cross Abstract: Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essen

Generative Refinement Networks for Visual Synthesis

arXiv:2604.13030v1 Announce Type: new Abstract: While diffusion models dominate the field of visual generation, they are computationally inefficient, applying a uniform computational effort regardless

GeoAlign: Geometric Feature Realignment for MLLM Spatial Reasoning

arXiv:2604.12630v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have exhibited remarkable performance in various visual tasks, yet still struggle with spatial reasoning. Rec

GeoPl@ntNet: A Platform for Exploring Essential Biodiversity Variables

arXiv:2511.13790v2 Announce Type: replace-cross Abstract: This paper describes GeoPl@ntNet, an interactive web application designed to make Essential Biodiversity Variables accessible and understandab

GF-Score: Certified Class-Conditional Robustness Evaluation with Fairness Guarantees

arXiv:2604.12757v1 Announce Type: cross Abstract: Adversarial robustness is essential for deploying neural networks in safety-critical applications, yet standard evaluation methods either require expe

GGD-SLAM: Monocular 3DGS SLAM Powered by Generalizable Motion Model for Dynamic Environments

arXiv:2604.12837v1 Announce Type: new Abstract: Visual SLAM algorithms achieve significant improvements through the exploration of 3D Gaussian Splatting (3DGS) representations, particularly in generat

applicationsarxiv-cs-ro

Local Ai

GigaCheck: Detecting LLM-generated Content via Object-Centric Span Localization

arXiv:2410.23728v3 Announce Type: replace Abstract: With the increasing quality and spread of LLM assistants, the amount of generated content is growing rapidly. In many cases and tasks, such texts ar

local-aiarxiv-cs-cl

GLeMM: A large-scale multilingual dataset for morphological research

arXiv:2604.12442v1 Announce Type: new Abstract: In derivational morphology, what mechanisms govern the variation in form-meaning relations between words? The answers to this type of questions are typi

researcharxiv-cs-cl

Global optimization tailored for graphics processing units: Complete and rigorous search for large-scale nonlinear minimization

arXiv:2507.01770v4 Announce Type: replace-cross Abstract: This paper introduces a numerical method to enclose the global minimum of a nonlinear function subject to simple bounds on the variables. Usin

GlotOCR Bench: OCR Models Still Struggle Beyond a Handful of Unicode Scripts

model-releasesarxiv-cs-cl

arXiv:2604.12978v1 Announce Type: new Abstract: Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cl

Goal-Conditioned Neural ODEs with Guaranteed Safety and Stability for Learning-Based All-Pairs Motion Planning

arXiv:2604.02821v2 Announce Type: replace Abstract: This paper presents a learning-based approach for all-pairs motion planning, where the initial and goal states are allowed to be arbitrary points in

safetyarxiv-cs-ro

GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responses

arXiv:2604.11924v1 Announce Type: new Abstract: While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to auto

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization

arXiv:2604.11810v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. However, their immense number

GRADE: Probing Knowledge Gaps in LLMs through Gradient Subspace Dynamics

arXiv:2604.02830v2 Announce Type: replace Abstract: Detecting whether a model's internal knowledge is sufficient to correctly answer a given question is a fundamental challenge in deploying responsibl

applicationsarxiv-cs-cl

Gradient boundaries through confidence intervals for forced alignment estimates using model ensembles

arXiv:2506.01256v4 Announce Type: replace-cross Abstract: Forced alignment is a common tool to align audio with orthographic and phonetic transcriptions. Most forced alignment tools provide only point

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs

arXiv:2206.00939v3 Announce Type: replace-cross Abstract: The training of neural networks by gradient descent methods is a cornerstone of the deep learning revolution. Yet, despite some recent progres

safetyarxiv-cs-lg

Graph-Based Chain-of-Thought Pruning for Reducing Redundant Reflections in Reasoning LLMs

arXiv:2604.05643v2 Announce Type: replace Abstract: Extending CoT through RL has been widely used to enhance the reasoning capabilities of LLMs. However, due to the sparsity of reward signals, it can

Grasp in Gaussians: Fast Monocular Reconstruction of Dynamic Hand-Object Interactions

arXiv:2604.12929v1 Announce Type: new Abstract: We present Grasp in Gaussians (GraG), a fast and robust method for reconstructing dynamic 3D hand-object interactions from a single monocular video. Unl

safetyarxiv-cs-cv

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling

arXiv:2511.05477v2 Announce Type: replace Abstract: Medical image segmentation demands models that achieve high accuracy while maintaining computational efficiency and clinical interpretability. While

Growing Pains: Extensible and Efficient LLM Benchmarking Via Fixed Parameter Calibration

model-releasesarxiv-cs-cl

arXiv:2604.12843v1 Announce Type: new Abstract: The rapid release of both language models and benchmarks makes it increasingly costly to evaluate every model on every dataset. In practice, models are

GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection

arXiv:2510.07285v3 Announce Type: replace-cross Abstract: The escalating complexity of network threats and the inherent class imbalance in traffic data present formidable challenges for modern Intrusi