Search: “evaluation”

Efficient Task Adaptation in Large Language Models via Selective Parameter Optimization

arXiv:2604.17051v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated excellent performance in general language understanding, generation and other tasks. However, when fine-t

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EgoSound: Benchmarking Sound Understanding in Egocentric Videos

DGX agent

arXiv:2602.14122v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have recently achieved remarkable progress in vision-language understanding. Yet, human perception is inher

model-releasesarxiv-cs-cv

21 Apr 2026

EgoWalk: A Multimodal Dataset for Robot Navigation in the Wild

arXiv:2505.21282v2 Announce Type: replace Abstract: Data-driven navigation algorithms are critically dependent on large-scale, high-quality real-world data collection for successful training and robus

applicationsarxiv-cs-ro

Embedding Arithmetic: A Lightweight, Tuning-Free Framework for Post-hoc Bias Mitigation in Text-to-Image Models

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

EmbodiedLGR: Integrating Lightweight Graph Representation and Retrieval for Semantic-Spatial Memory in Robotic Agents

model-releasesarxiv-cs-ro

arXiv:2604.18271v1 Announce Type: new Abstract: As the world of agentic artificial intelligence applied to robotics evolves, the need for agents capable of building and retrieving memories and observa

Employing General-Purpose and Biomedical Large Language Models with Advanced Prompt Engineering for Pharmacoepidemiologic Study Design

arXiv:2604.17988v1 Announce Type: new Abstract: Background: The potential of large language models (LLMs) to automate and support pharmacoepidemiologic study design is an emerging area of interest, ye

Empowering Multi-Turn Tool-Integrated Agentic Reasoning with Group Turn Policy Optimization

arXiv:2511.14846v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) for multi-turn Tool-Integrated Reasoning (TIR) - where models iteratively reason, generate code, and ver

End-to-End Optimization of LLM-Driven Multi-Agent Search Systems via Heterogeneous-Group-Based Reinforcement Learning

arXiv:2506.02718v2 Announce Type: replace Abstract: Large language models (LLMs) are versatile, yet their deployment in complex real-world settings is limited by static knowledge cutoffs and the diffi

safetyarxiv-cs-lg

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning

arXiv:2412.02904v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized the field of natural language processing with their impressive reasoning and question-answering cap

ENTIRE: Learning-based Volume Rendering Time Prediction

arXiv:2501.12119v3 Announce Type: replace-cross Abstract: We introduce ENTIRE, a novel deep learning-based approach for fast and accurate volume rendering time prediction. Predicting rendering time is

Evidence-Augmented Policy Optimization with Reward Co-Evolution for Long-Context Reasoning

arXiv:2601.10306v2 Announce Type: replace-cross Abstract: While Reinforcement Learning (RL) has advanced LLM reasoning, applying it to long-context scenarios is hindered by sparsity of outcome rewards

Evolutionary Negative Module Pruning for Better LoRA Merging

arXiv:2604.17753v1 Announce Type: cross Abstract: Merging multiple Low-Rank Adaptation (LoRA) experts into a single backbone is a promising approach for efficient multi-task deployment. While existing

Explaining Uncertainty in Multiple Sclerosis Cortical Lesion Segmentation Beyond Prediction Errors

arXiv:2504.04814v3 Announce Type: replace-cross Abstract: Trustworthy artificial intelligence (AI) is essential in healthcare, particularly for high-stakes tasks like medical image segmentation. Expla

applicationsarxiv-cs-cv

Explanation Bias is a Product: Revealing the Hidden Lexical and Position Preferences in Post-Hoc Feature Attribution

arXiv:2512.11108v3 Announce Type: replace Abstract: Good quality explanations strengthen the understanding of language models and data. Feature attribution methods, such as Integrated Gradient, are a

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD

arXiv:2604.18491v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is central to race-car aerodynamic development, yet its cost -- tens of thousands of core-hours per high-fidelity eva

researcharxiv-cs-lg

FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling

arXiv:2604.16574v1 Announce Type: new Abstract: Federated Learning (FL) faces challenges from client data heterogeneity and resource-constrained mobile devices, which can degrade model accuracy. Perso

FireScope: Wildfire Risk Prediction with a Chain-of-Thought Oracle

arXiv:2511.17171v4 Announce Type: replace Abstract: Predicting wildfire risk is a reasoning-intensive spatial problem that requires the integration of visual, climatic, and geographic factors to infer

FLiP: Towards understanding and interpreting multimodal multilingual sentence embeddings

arXiv:2604.18109v1 Announce Type: new Abstract: This paper presents factorized linear projection (FLiP) models for understanding pretrained sentence embedding spaces. We train FLiP models to recover t

Flow marching for a generative PDE foundation model

arXiv:2509.18611v2 Announce Type: replace Abstract: Pretraining on large-scale collections of PDE-governed spatiotemporal trajectories has recently shown promise for building generalizable models of d

FoleyDirector: Fine-Grained Temporal Steering for Video-to-Audio Generation via Structured Scripts

arXiv:2603.19857v2 Announce Type: replace-cross Abstract: Recent Video-to-Audio (V2A) methods have achieved remarkable progress, enabling the synthesis of realistic, high-quality audio. However, they

Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality

arXiv:2505.11140v3 Announce Type: replace Abstract: We introduce fs1, a simple yet effective method that improves the factuality of reasoning traces by collecting them from large reasoning models and

Foundational Study on Authorship Attribution of Japanese Web Reviews for Actor Analysis

arXiv:2604.16376v1 Announce Type: new Abstract: This study investigates the applicability of authorship attribution based on stylistic features to support actor analysis in threat intelligence. As a f

Frankentext: Stitching random text fragments into long-form narratives

arXiv:2505.18128v4 Announce Type: replace Abstract: We introduce Frankentexts, a long-form narrative generation paradigm that treats an LLM as a composer of existing texts rather than as an author. Gi

Freshness-Aware Prioritized Experience Replay for LLM/VLM Reinforcement Learning

arXiv:2604.16918v1 Announce Type: new Abstract: Reinforcement Learning (RL) has achieved impressive success in post-training Large Language Models (LLMs) and Vision-Language Models (VLMs), with on-pol

Local Ai

Fringe Projection Based Vision Pipeline for Autonomous Hard Drive Disassembly

arXiv:2604.17231v1 Announce Type: new Abstract: Unrecovered e-waste represents a significant economic loss. Hard disk drives (HDDs) comprise a valuable e-waste stream necessitating robotic disassembly

local-aiarxiv-cs-cv

From Attribution to Abstention: Training-Free Attention-Based Auditing for Clinical Summarization

arXiv:2601.16397v2 Announce Type: replace Abstract: Deploying multimodal large language models (MLLMs) for clinical summarization demands not only fluent generation but also transparency about where e

Agents

From Clinical Intent to Clinical Model: An Autonomous Coding-Agent Framework for Clinician-driven AI Development

arXiv:2604.17110v1 Announce Type: new Abstract: Clinical AI development has traditionally followed a collaborative paradigm that depends on close interaction between clinicians and specialized AI team

agentsarxiv-cs-cv

From Handwriting to Structured Data: Benchmarking AI Digitisation of Handwritten Forms

arXiv:2604.16504v1 Announce Type: new Abstract: Manual digitisation of structured handwritten documents is slow and costly. We benchmark 17 leading frontier multi-modal large language models and open-

Function Words as Statistical Cues for Language Learning

arXiv:2601.21191v2 Announce Type: replace Abstract: What statistical properties might support learning abstract grammatical knowledge from linear input? We address this question by examining the stati

Functional Similarity Metric for Neural Networks: Overcoming Parametric Ambiguity via Activation Region Analysis

arXiv:2604.16426v1 Announce Type: new Abstract: As modern deep learning architectures grow in complexity, representational ambiguity emerges as a critical barrier to their interpretability and reliabl

Generalizable Face Forgery Detection via Separable Prompt Learning

arXiv:2604.17307v1 Announce Type: new Abstract: Detecting face forgeries using CLIP has recently emerged as a promising and increasingly popular research direction. Owing to its rich visual knowledge

Generalization Boundaries of Fine-Tuned Small Language Models for Graph Structural Inference

arXiv:2604.18092v1 Announce Type: new Abstract: Small language models fine-tuned for graph property estimation have demonstrated strong in-distribution performance, yet their generalization capabiliti

GeoRC: A Benchmark for Geolocation Reasoning Chains

arXiv:2601.21278v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) are good at recognizing the global location of a photograph -- their geolocation prediction accuracy rivals the

GoCoMA: Hyperbolic Multimodal Representation Fusion for Large Language Model-Generated Code Attribution

arXiv:2604.16377v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on massive code corpora are now increasingly capable of generating code that is hard to distinguish from human-writ

Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization

arXiv:2604.16496v1 Announce Type: cross Abstract: Continual learning, the ability to acquire new tasks sequentially without forgetting prior knowledge, is essential for deploying neural networks in dy

applicationsarxiv-cs-lg

Harness as an Asset: Enforcing Determinism via the Convergent AI Agent Framework (CAAF)

arXiv:2604.17025v1 Announce Type: cross Abstract: Large Language Models (LLMs) produce a controllability gap in safety-critical engineering: even low rates of undetected constraint violations render a

How Non-Linguistic Is the Indus Sign System? A Synthetic-Baseline Scorecard

arXiv:2604.17828v1 Announce Type: new Abstract: Whether the Indus Valley sign system (c. 2600-1900 BCE) encodes spoken language has been debated for decades. This paper introduces a multi-metric discr

applicationsarxiv-cs-cl

Tutorials

How to Approximate Inference with Subtractive Mixture Models

arXiv:2604.16714v1 Announce Type: new Abstract: Classical mixture models (MMs) are widely used tractable proposals for approximate inference settings such as variational inference (VI) and importance

tutorialsarxiv-cs-lg

Agents

Human Cognition in Machines: A Unified Perspective of World Models

arXiv:2604.16592v1 Announce Type: cross Abstract: This comprehensive report distinguishes prior works by the cognitive functions they innovate. Many works claim an almost 'human-like' cognitive capabi

agentsarxiv-cs-cv

Hybrid-Vector Retrieval for Visually Rich Documents: Combining Single-Vector Efficiency and Multi-Vector Accuracy

arXiv:2510.22215v2 Announce Type: replace-cross Abstract: Retrieval over visually rich documents is essential for tasks such as legal discovery, scientific search, and enterprise knowledge management.

HyKey: Hyperspectral Keypoint Detection and Matching in Minimally Invasive Surgery

arXiv:2604.17446v1 Announce Type: new Abstract: Purpose: 3D reconstruction in minimally invasive surgery (MIS) enables enhanced surgical guidance through improved visualisation, tool tracking, and aug

IMA-MoE: An Interpretable Modality-Aware Mixture-of-Experts Framework for Characterizing the Neurobiological Signatures of Binge Eating Disorder

arXiv:2604.17028v1 Announce Type: new Abstract: Binge eating disorder (BED) is the most prevalent eating disorder. However, current diagnostic frameworks remain largely grounded in symptom-based crite

Implicit neural representations as a coordinate-based framework for continuous environmental field reconstruction from sparse ecological observations

arXiv:2604.18083v1 Announce Type: new Abstract: Reconstructing continuous environmental fields from sparse and irregular observations remains a central challenge in environmental modelling and biodive

safetyarxiv-cs-lg

Improving Dynamic Object Interactions in Text-to-Video Generation with AI Feedback

arXiv:2412.02617v2 Announce Type: replace-cross Abstract: Large text-to-video models hold immense potential for a wide range of downstream applications. However, they struggle to accurately depict dyn

safetyarxiv-cs-cv

In Situ Training of Implicit Neural Compressors for Scientific Simulations via Sketch-Based Regularization

arXiv:2511.02659v3 Announce Type: replace Abstract: Focusing on implicit neural representations, we present a novel in situ training protocol that employs limited memory buffers of full and sketched d

researcharxiv-cs-lg

Incentivizing Parametric Knowledge via Reinforcement Learning with Verifiable Rewards for Cross-Cultural Entity Translation

arXiv:2604.16881v1 Announce Type: new Abstract: Cross-cultural entity translation remains challenging for large language models (LLMs) as literal or phonetic renderings are usually yielded instead of

Incoherent Deformation, Not Capacity: Diagnosing and Mitigating Overfitting in Dynamic Gaussian Splatting

arXiv:2604.16747v1 Announce Type: new Abstract: Dynamic 3D Gaussian Splatting methods achieve strong training-view PSNR on monocular video but generalize poorly: on the D-NeRF benchmark we measure an

Inference-Time Temporal Probability Smoothing for Stable Video Segmentation with SAM2 under Weak Prompts

arXiv:2604.17115v1 Announce Type: new Abstract: Interactive video segmentation models such as SAM2 have demonstrated strong generalization across diverse visual domains. However, under weak user super