Search: “model-releases”

DynaContext: Self-Improving Dynamic Contextualization of Optimized Prompts for Heterogeneous Parameter Extraction

arXiv:2608.22014v1 Announce Type: new Abstract: Automated prompt and skill optimization typically produces a single static instruction that is reused across inference instances until the next optimiza

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Model Releases

EarthVerse: Benchmarking Scientific Agents Across Dynamic Earth Systems and Natural Hazards

DGX agent

arXiv:2608.23525v1 Announce Type: new Abstract: Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards mak

model-releasesarxiv-cs-ai

25 Aug 2026

Effects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of LLMs in Ultimatum Games

arXiv:2505.24255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for com

EG-ARSA: An Expert-Grounded Open Model for Visual Road Safety Auditing in Low-Resource Settings

arXiv:2608.23563v1 Announce Type: cross Abstract: Road traffic injuries remain a major challenge in low- and middle-income countries, where proactive road safety auditing is limited by incomplete cras

ENCORE: Entropy-Guided Cropping and Attention Regularization for Robust Vision--Language Understanding

arXiv:2608.22996v1 Announce Type: new Abstract: Vision-Language Models (VLMs) perform well on diverse vision-language tasks, but transformer-based visual encoders split images into fixed-resolution su

Enhancing Sim2Real Transfer for Torque-Controlled Robots through Real2Sim Dynamics Estimation and Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2608.22629v1 Announce Type: new Abstract: Transferring reinforcement learning policies from simulation to Real-World robots remains a major challenge, particularly when dealing with low-level to

Entity-Constrained CBCT Retrieval for Low-Resource Dental Record Completion

arXiv:2608.21913v1 Announce Type: new Abstract: Completing dental records from cone-beam computed tomography (CBCT) is difficult when annotation is scarce and individual clinical fields are supported

ESCRAG-R1: Retrieval-Augmented Reinforcement Learning for Emotional Support Conversation

arXiv:2608.21925v1 Announce Type: new Abstract: Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. Howe

Evaluating Large Language Models for automatic analysis of teacher simulations

arXiv:2407.20360v2 Announce Type: replace Abstract: Digital Simulations (DS) provide safe environments where users interact with an agent through conversational prompts, providing engaging learning ex

Evaluating Multimodal Narrative Understanding of Popular Hollywood Films

arXiv:2608.21430v1 Announce Type: new Abstract: Multimodal language models increasingly show promise for enabling the large-scale computational analysis of film, opening up new avenues for learning ab

Evaluating the Efficacy of LLMs to Emulate Realistic Human Personalities

arXiv:2402.14879v2 Announce Type: replace-cross Abstract: To enhance immersion and engagement in video games, the design of Affective Non-Player Characters (ANPCs) is a key focus for researchers and p

Evaluation of Small Vision-Language Models on Qualitative Mechanical Problems

arXiv:2608.22143v1 Announce Type: new Abstract: Qualitative mechanical problem-solving (QMPS) refers to solving qualitative problems from the mechanical domain. Qualitative problems can be solved with

EviSafe: Evidence-Grounded Safety Evaluation for Vision-Language Models

arXiv:2608.23313v1 Announce Type: new Abstract: Vision-language model safety benchmarks typically evaluate only final responses: whether a model refuses, warns, or complies. This outcome-level view ca

EvoWiki: Incremental State Overwriting and Traceable Question Answering for Cross-Meeting Knowledge Evolution

arXiv:2608.23265v1 Announce Type: new Abstract: In long-term collaboration spanning multiple meetings, factual states such as decisions and risks are continually revised, overturned, and replaced. Exi

Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation

arXiv:2409.16183v2 Announce Type: replace Abstract: Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in me

EXPL-FR: Explaining Face Recognition Models via Vision-Language Alignment

arXiv:2608.21486v1 Announce Type: new Abstract: Deep face recognition (FR) models reach near-saturated accuracy but remain opaque: a practitioner cannot ask which semantic attributes a similarity scor

ExplainGuard: A Zero Trust Framework for Post-Hoc Explanation Integrity Guarantees in Blackbox XAI Models

arXiv:2608.21803v1 Announce Type: cross Abstract: As machine learning (ML) models are increasingly deployed in high-stakes environments, explainable AI (XAI) methods like SHAP and LIME have become ess

ExtrinSplat: Decoupling Geometry and Semantics for Open-Vocabulary Understanding in 3D Gaussian Splatting

arXiv:2509.22225v3 Announce Type: replace-cross Abstract: Lifting 2D open-vocabulary understanding into 3D Gaussian Splatting (3DGS) scenes is a critical challenge. Mainstream methods, built on an emb

Fairness-Aware Low-Rank Representation Fine-Tuning

arXiv:2503.05684v2 Announce Type: replace-cross Abstract: Pre-trained foundation models can be efficiently adapted for specific tasks using Low-Rank Adaptation (LoRA), but the fairness properties of t

Federated Continual Learning as a Distributed Drift-Plus-Penalty Control Problem

arXiv:2608.21539v1 Announce Type: new Abstract: Federated Continual Learning (FCL) is fundamental to real-world distributed learning systems, requiring models to adapt to sequential, non-IID data acro

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection

arXiv:2509.10041v2 Announce Type: replace Abstract: Federated learning (FL) enables collaborative model training without centralizing data, but exchanging high-dimensional updates can expose sensitive

Fidelity-Diversity-Consistency (FDC): Data Pruning for Remote Sensing Change Detection

arXiv:2608.21754v1 Announce Type: new Abstract: Despite the success of data pruning (DP) in reducing training data sizes and improving downstream model performance in classification and segmentation t

FigmaTrace: Capturing Creative Nuances in Human Figma Design Workflows

arXiv:2608.21460v1 Announce Type: cross Abstract: Vision Language Models have recently shown improvements in several objective and verifiable domains such as object detection but continue to underperf

FinixDoc: Rethinking Financial Document Parsing Beyond Saturated Benchmarks

arXiv:2608.22842v1 Announce Type: new Abstract: Financial document parsing requires accuracy, structural consistency, and verifiability that current benchmarks often fail to reflect. We present FinixD

Frame-Level Evaluation in Weakly Supervised Video Anomaly Detection Mostly Measures Video-Level Ranking

arXiv:2608.21854v1 Announce Type: new Abstract: Weakly supervised video anomaly detectors are trained with video-level labels but are commonly evaluated as temporal localizers using Micro-AUROC or AP

From Inertia to Objectivity: Improving Deep Research Agents with Noise Isolation

arXiv:2608.23045v1 Announce Type: new Abstract: Web search agents powered by Large Language Models (LLMs) show strong promise, but deep research tasks expose a recurring failure mode: once an agent ha

From Isolation to Alignment: Unified LoRA for Efficient Multi-Task Learning

arXiv:2508.05078v2 Announce Type: replace-cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is essential for adapting Large Language Models (LLMs) to multi-task scenarios. A prevailing trend in t

From Mastery Profile to Simulated Response: Stochastic Student Knowledge Graphs (SSKG) for Faithful LLM Student Simulation

arXiv:2608.21668v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate students at different mastery levels. These simulations can generate synthetic training d

From SQL Generation to Tool Selection: A Domain-Oriented Pattern for MCP Servers

arXiv:2608.22063v1 Announce Type: new Abstract: Agents built on Large Language Models (LLMs) increasingly reach enterprise data through the Model Context Protocol (MCP), and many MCP database servers

From Subjective Judgments to Auditable Standards:Protocol-Guided AI Auditing of Website Redundancy

arXiv:2608.21476v1 Announce Type: cross Abstract: Website redundancy does not have a single fixed meaning. The same repeated element may distract during one task and provide backup during another. We

GameXpert-Bench: How Far Are Coding Agents from Expert Game Development?

arXiv:2608.21833v1 Announce Type: new Abstract: Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especiall

GAN-Diff : Coupling Pretrained WGAN-GP Features with Conditional Diffusion U-Nets

arXiv:2608.22272v1 Announce Type: cross Abstract: Generative adversarial networks (GANs) can provide efficient image generation, while diffusion models offer high-quality image restoration but require

Gated Decoupled Compositional Bandits: A Unified Theory of Contextual Bandits with Supervised-Calibrated Action Scaling and Pre-Execution Gating

arXiv:2608.21993v1 Announce Type: new Abstract: We introduce Gated Decoupled Compositional Bandits (GDCB), a family of contextual bandit algorithms with three structural innovations that jointly fall

Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate

arXiv:2608.21467v1 Announce Type: cross Abstract: Gaussian distributions are used to model uncertainty in signals and states, and Gaussian mixtures are often used when the underlying distribution is m

Gaussian process learning with flow map refinement for parameter estimation in dynamical systems

arXiv:2608.22324v1 Announce Type: new Abstract: Parameter estimation is a central task in data-driven learning of dynamical systems. It aims to recover the underlying physical parameters from observed

GRACE: Step-Level Benchmark for Faithful Reasoning over Context

arXiv:2606.16151v2 Announce Type: replace Abstract: Many reasoning tasks require models to reason over input context, from document-grounded question answering to rule-based deduction. Chain-of-Though

Grounded Normative Rule Generation with Structured Search

arXiv:2608.22229v1 Announce Type: new Abstract: Normative rules like institutional charters and workplace policies must be both human-readable and operationally verifiable against actual environment r

GSAR: Goal-State-Anchor Rewards for Mobile GUI Agents with Self-Evolving Data Synthesis

arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle

GuardianBench: A Same-Scene Instruction-Contrastive Benchmark for Latent Contextual Risk in Embodied AI

arXiv:2608.21928v1 Announce Type: new Abstract: In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied s

GUI-Primitives: Diagnosing Spatial Reasoning Failures in Vision-Language GUI Grounding

arXiv:2608.21832v1 Announce Type: new Abstract: Computer-use agents ground natural-language instructions in screenshots to locate interface elements, yet existing benchmarks do not isolate whether mod

Guidance for Prior Change via Density Ratio Estimation

arXiv:2608.21729v1 Announce Type: cross Abstract: Simulation-Based Inference (SBI) serves as a vital framework for parameter inference in scientific fields where simulators involve intractable likelih

Guided Riemannian Optimization (GuRO): Bridging Model Predictive Control and Decision Transformers

model-releasesarxiv-cs-ro

arXiv:2608.23204v1 Announce Type: new Abstract: Decision-making in high-dimensional, nonlinear systems remains a central challenge in robotics. While model-based methods like Model Predictive Control

Hack-Verifiable Terminal Bench: Evaluating Reward Hacking in Terminal Tasks

arXiv:2608.22103v1 Announce Type: new Abstract: As agents grow more capable and autonomous, their tendency to reward hack, satisfying a task's checks while violating its intent, becomes an increasingl

Hate Speech Classification In Roman Urdu: A Comparative Study On Parameter Efficient Fine-Tuning And Prompt Engineering

arXiv:2608.21408v1 Announce Type: new Abstract: Due to the widespread accessibility of the internet and social media, toxic and hateful con-tent has grown exponentially, causing significant distress a

HAWKEYE: Seeing One Layer Deeper -- A Cohesion-Aware Structural Channel for Temporal Link Prediction

arXiv:2608.22727v1 Announce Type: cross Abstract: State-of-the-art temporal-link-prediction (TLP) models are, in essence, multi-channel information aggregators: they combine an interaction-history cha

HERO: Human-profile Enhanced Retrieval Optimization Framework for Long-term Agent Memory

arXiv:2608.22310v1 Announce Type: new Abstract: Long-term memory is crucial for personalized responses and long-horizon agent interactions. Existing methods often rely on LLMs to compress or rewrite d

Hierarchical Book Organization for Learning-Resource Discovery using Dual-Path Graph Convolutions

arXiv:2512.21076v2 Announce Type: replace-cross Abstract: The growing availability of books and textual materials in digital learning environments necessitates reliable semantic organization to suppor

Hierarchical Exponential-Gaussian Mixtures for Watch-Time Distribution Prediction

arXiv:2608.23356v1 Announce Type: cross Abstract: Accurate watch-time (WT) prediction is an important requirement for short-video recommendations. Yet WT distributions are near-zero-inflated, long-tai