Search: “model-releases”

Evidence-Bounded Mental Health Reasoning from Heterogeneous Speech Protocols

arXiv:2608.31014v1 Announce Type: new Abstract: Computational mental health screening using multimodal speech and text has shown great promise. However, existing models often assume all clinical speec

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Model Releases

EvoBrowseComp: Benchmarking Search Agents on Evolving Knowledge

DGX agent

arXiv:2606.13120v2 Announce Type: replace Abstract: Search Agents -- large language models augmented with search tools -- have intensified the need for future-proof evaluation benchmarks. Existing ben

model-releasesarxiv-cs-cl

1 Sept 2026

EvoGenUI-Bench: Evaluating LLMs as Multi-Turn Generative UI Assistants

arXiv:2608.29387v1 Announce Type: new Abstract: Large language models can generate interactive web interfaces, but reliable generative UI requires maintaining an executable artifact as user requests e

EvoSkill Injection: Red-Teaming Autonomous Skill Generation and Evolution in Self-Evolving Agents

arXiv:2608.30429v1 Announce Type: new Abstract: LLM-based agent systems increasingly adopt skill-based architectures to reduce repetitive reasoning costs and improve stable, efficient task execution.

Expert-validated STEM QA

arXiv:2608.28591v1 Announce Type: new Abstract: Recent advancements in AI are helping scientists achieve breakthroughs in fields such as mathematics, medicine, and materials sciences. New evaluation d

FaceSnap: Real-Time Personalized Lightstage Facial Performance Capture

arXiv:2608.31033v1 Announce Type: new Abstract: Lightstage facial capture produces production-quality digital humans, but it is resource and labor-intensive. Multi-camera setups, hours of computation,

Facts Without Rules: Boundary Metadata Collapse in Multi-Agent LLM Handoffs

arXiv:2608.29028v1 Announce Type: new Abstract: Multi-agent LLM systems often coordinate by compressing an upstream interaction into a handoff artifact that downstream agents treat as shared state. We

FigMirror: Ground It, Code It, Plot It

arXiv:2608.28814v1 Announce Type: cross Abstract: Converting scientific figures into executable code has gained increasing attention, yet existing methods primarily focus on reproducing the reference

Fine-Grained Multi Image Object Hallucination Benchmark

arXiv:2608.30653v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in multi-image scenarios requiring complex reasoning across visual contexts. Howeve

FORESIGHT-9: Prospective and Process-Aware Evaluation of Adaptive Trading Agents

arXiv:2608.29372v1 Announce Type: new Abstract: Retrospective backtests provide a limited test of adaptive trading agents: they cannot rule out historical contamination, expose sensitivity to a single

Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection

arXiv:2608.29802v1 Announce Type: new Abstract: Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Pres

Foundational feature fusion for conditional flow matching in 6D pose estimation

arXiv:2608.29183v1 Announce Type: new Abstract: Conditional flow matching has enabled a step forward in object 6D pose estimation, achieving state-of-the-art performance by progressively denoising and

FoundYou: A Unified Model for Personalized Segmentation and Retrieval

arXiv:2608.29917v1 Announce Type: new Abstract: Personalized segmentation and personalized retrieval both aim to identify the same physical object across different images. While the former localizes t

FRAC-MAS: A Safe and Explainable Multi-Agent System for Fracture Diagnosis

arXiv:2608.28662v1 Announce Type: new Abstract: Fracture detection and its clinical interpretability see notable improvements when deep vision models are integrated with agentic AI architectures. Whil

FractureFields: Contact-Aware Binary Multi-Field Transfer for Fractured 3D Gaussian Simulation

arXiv:2608.28982v1 Announce Type: new Abstract: Physics-integrated 3D Gaussian representations make it possible to simulate image-reconstructed assets directly as particles, but current Gaussia-MPM pi

Frequency Selective Neural Networks as a Foundation Architecture for Time Series Learning

arXiv:2608.29012v1 Announce Type: new Abstract: Time-series data across physical and biological domains are fundamentally driven by complex, non-stationary oscillatory modes. While deep learning model

From Location Phrases to Geographic Entities: Task-Adapted Retrieval for People Search

arXiv:2608.28965v1 Announce Type: new Abstract: People search must map free-form location phrases to geographic entities used as structured retrieval filters. Lexical standardizers handle canonical na

From Question-First to Analyst-First: Domain-Expert Skills and Verified Knowledge Compilation for Proactive Enterprise Analytics

arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar ente

From Speech to Subtitles: Evaluating ASR Models in Subtitling Italian Television Programs

arXiv:2512.19161v2 Announce Type: replace Abstract: Subtitles are essential for video accessibility and audience engagement. Modern Automatic Speech Recognition (ASR) systems, built upon Encoder-Decod

Frontier vision-language models have overtaken young adults at detecting AI-generated portraits -- but not their calibration

arXiv:2608.30210v1 Announce Type: cross Abstract: AI image generators now create face portraits that are hard to tell from real photographs. Vision-language models (VLMs) are increasingly proposed to

FuncRoom-Agent: Sequential Feed-Forward 3D Functional Indoor Scene Generation

arXiv:2608.29519v1 Announce Type: new Abstract: We introduce Function-Room Generation, a new indoor 3D scene generation setting that creates rooms supporting explicit functional goals rather than mere

Functional Degeneracy in Neural Networks: Measurement and Pruning

model-releasesarxiv-cs-lg

arXiv:2608.30741v1 Announce Type: new Abstract: A central question in modern machine learning is how much a trained model can be compressed without changing its behavior, to reduce the memory, compute

GAFT: Geo-Anchored Fine-Tuning for Hazard Identification from Rare Failures

arXiv:2608.30858v1 Announce Type: cross Abstract: Off-road navigation can fail when physical structures induce irrecoverable states such as high-centering or entrapment, requiring human interventions.

GATE: Reliability-Gated Gaussian Evidence Fusion for Training-Free Test-Time Adaptation of Vision-Language Models

arXiv:2608.29395v1 Announce Type: new Abstract: Vision-language models such as CLIP and SigLIP provide strong zero-shot recognition, but their predictions can degrade when deployed on target data that

General Phrase Debiaser: Debiasing Masked Language Models at a Multi-Token Level

arXiv:2311.13892v4 Announce Type: replace-cross Abstract: The social biases and unwelcome stereotypes revealed by pretrained language models are becoming obstacles to their application. Compared to nu

Generating Workflow DAGs from Natural Language with Non-Reasoning LLMs

arXiv:2608.30250v1 Announce Type: new Abstract: This paper addresses the problem of translating natural-language routing rules written by business administrators into executable workflow graphs for en

Generative vs. Encoder Models for Multilingual NER: A Comprehensive Empirical Study on Naamapadam

arXiv:2608.29959v1 Announce Type: new Abstract: Language is humanity's most consequential technology, yet for over a billion speakers across India's twenty-two constitutionally recognised languages, i

GeoAgent: Evaluating VLM Geolocalization Through Embodied Navigation

arXiv:2608.29483v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) perform well above the human baseline in image geolocalization, a task critically important in disaster response,

GeoRay: Gauge-Aware Feed-Forward Satellite 3D Reconstruction in the Geodetic Frame

arXiv:2608.29680v1 Announce Type: new Abstract: Feed-forward 3D foundation models reconstruct perspective scenes in one pass. Satellite photogrammetry needs a different product, one that domain adapta

GPAgentBench-2K: Benchmarking Large Language Model Agents in Complex Clinical Action Space

arXiv:2608.30188v1 Announce Type: new Abstract: Large Language Models (LLMs) show great potential as clinical agents, yet existing benchmarks reduce clinical workflows to static predictions or unconst

GramLoop: Training-Free Gram-Gated Replay for Robust Dense Prediction

arXiv:2608.29113v1 Announce Type: new Abstract: We aim to improve frozen DINOv3 dense-prediction models under distribution shift by adding inference computation inside the visual backbone, without cha

GreenBench: Benchmarking Energy Efficiency and Carbon Footprint of Open-Source LLM Inference on Apple Silicon

arXiv:2608.28667v1 Announce Type: cross Abstract: The rapid proliferation of Large Language Models (LLMs) has raised concerns about their environmental impact during inference. While Green AI research

GridFlow: Structured Latent Flow for Seamless City-Scale 3D Point Cloud Generation

arXiv:2608.29793v1 Announce Type: new Abstract: Generating realistic 3D city environments from remote sensing data is important for simulation, urban planning, and mixed reality, yet existing point cl

Guardrail-Agnostic Societal Bias Evaluation in Large Vision-Language Models

arXiv:2608.29590v1 Announce Type: new Abstract: We propose a societal bias evaluation method for large vision-language models (LVLMs) in the era of strong safety guardrails. Existing benchmarks rely o

GUI-PRA: Process Reward Agent for GUI Tasks

arXiv:2509.23263v3 Announce Type: replace Abstract: Long-horizon GUI automation remains challenging due to error accumulation over extended interaction sequences. Process Reward Models (PRMs) provide

GUIDE: Guiding Internal Evidence with Language Instructions

arXiv:2608.30712v1 Announce Type: new Abstract: Large multimodal models follow instructions about what to generate, but not necessarily about what evidence to rely on. Hence, models may continue to de

Gurukul AI: An Interactive AI-Driven Educational Platform for Indian Education System

arXiv:2608.28611v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) like ChatGPT and LLaMA have transformed AI-driven education, but these systems are predominantly train

HEAR Who Said What: Unlocking Speaker-Attributed Reasoning via Counterfactual Voice Grounding

arXiv:2608.29120v1 Announce Type: cross Abstract: Speech Language Models (SLMs) are increasingly deployed in multi-speaker environments, yet their ability to attribute speech to the correct speaker an

HeTGB: A Comprehensive Benchmark for Heterophilic Text-Attributed Graphs

arXiv:2503.04822v2 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) have demonstrated success in modeling relational data primarily under the assumption of homophily. However, many

HiRS-Agent: A Hierarchical Multi-Agent System for Reliable Long-Horizon Remote Sensing Task Solving

arXiv:2608.30672v1 Announce Type: new Abstract: Recent advances in large language models and multimodal models have pushed remote sensing (RS) processing from simple perception models to agentic syste

HiVe: Beyond Static Prompts for Multitask Learning via Hierarchy-based Vertical Mixture-of-Experts

arXiv:2608.29790v1 Announce Type: new Abstract: As large language models (LLMs) continue to scale, parameter-efficient fine-tuning (PEFT) has become a practical alternative to full-parameter adaptatio

How do World Models and Policies Compose in LLM Agents? A Joint Spectral and Behavioral Account

arXiv:2608.30067v1 Announce Type: cross Abstract: How do LLM agents come to both understand environments they act in and master tasks set within them? Through controlled experiments combining world-mo

How Language Models Choose Sides: Internal Representations of Instruction Hierarchy

arXiv:2608.28648v1 Announce Type: new Abstract: We study how instruction-tuned LLMs arbitrate direct conflicts between system and user instructions. We introduce a benchmark of 41 paired constraints w

How Order-Sensitive Are LLMs? OrderProbe for Deterministic Structural Reconstruction

arXiv:2601.08626v4 Announce Type: replace Abstract: Large language models (LLMs) excel at semantic understanding, yet their ability to reconstruct internal structure from scrambled inputs remains unde

HSRM: Hidden-State Reward Models for Test-Time Verification

arXiv:2608.30841v1 Announce Type: new Abstract: Large language models can often generate plausible mathematical reasoning traces, but reliably identifying the correct solution among multiple candidate

Ideation Arena: Evaluating LLM Generated Research Ideas with Battle-style Human Expert Assessment

arXiv:2608.29696v1 Announce Type: new Abstract: Evaluating research ideas generated by LLMs is difficult because their scientific value cannot be fully determined by objective criteria, and no single

Imag-Eval: a language-grounded framework for interpretable Text-to-Image instruction following evaluation

arXiv:2608.29210v1 Announce Type: new Abstract: Text-to-Image (T2I) models have recently achieved impressive visual fidelity, yet their evaluation remains constrained by benchmarks that are often diff

ImageCAS-X: a dataset and benchmark for coronary artery segmentation and centerline extraction in coronary CT angiography

arXiv:2608.30404v1 Announce Type: cross Abstract: Accurate segmentation of the coronary vessel lumen is a prerequisite for quantitative assessment of atherosclerotic plaque and perivascular adipose ti