Search: “gpt”

SOLAR: Communication-Efficient Model Adaptation via Subspace-Oriented Latent Adapter Reparametrization

model-releasesarxiv-cs-cl

arXiv:2604.08368v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, enable scalable adaptation of foundation models by injecting low-rank adapters. However,

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Spatio-Temporal Grounding of Large Language Models from Perception Streams

DGX agent

arXiv:2604.07592v1 Announce Type: new Abstract: Embodied-AI agents must reason about how objects move and interact in 3-D space over time, yet existing smaller frontier Large Language Models (LLMs) st

model-releasesarxiv-cs-ro

10 Apr 2026

Research

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training

arXiv:2604.06836v2 Announce Type: new Abstract: Quantization is an effective way to reduce the memory cost of large-scale model training. However, most existing methods adopt fixed-precision policies,

researcharxiv-cs-lg

SUPERGLASSES: Benchmarking Vision Language Models as Intelligent Agents for AI Smart Glasses

model-releasesarxiv-cs-cv

arXiv:2602.22683v2 Announce Type: replace Abstract: The rapid advancement of AI-powered smart glasses-one of the hottest wearable devices-has unlocked new frontiers for multimodal interaction, with Vi

Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval

model-releasesarxiv-cs-cv

arXiv:2512.08410v2 Announce Type: replace Abstract: Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose

TR-EduVSum: A Turkish-Focused Dataset and Consensus Framework for Educational Video Summarization

model-releasesarxiv-cs-cl

arXiv:2604.07553v1 Announce Type: new Abstract: This study presents a framework for generating the gold-standard summary fully automatically and reproducibly based on multiple human summaries of Turki

VisCoder2: Building Multi-Language Visualization Coding Agents

model-releasesarxiv-cs-ai

arXiv:2510.23642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently enabled coding agents capable of generating, executing, and revising visualization code. However, e

When to Call an Apple Red: Humans Follow Introspective Rules, VLMs Don't

model-releasesarxiv-cs-ai

arXiv:2604.06422v1 Announce Type: cross Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adher