Search: “models”

arXiv:2604.22812v1 Announce Type: cross Abstract: STEM dropout rates remain high at universities, particularly in computer science programs with theory-intensive courses. Digital learning environments

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LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models

DGX agent

arXiv:2604.23809v1 Announce Type: new Abstract: Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity s

applicationsarxiv-cs-cl

28 Apr 2026

Hardware

Non-Destructive Prediction of Fruit Ripeness and Firmness Using Hyperspectral Imaging and Lightweight Machine Learning Models

arXiv:2604.22788v1 Announce Type: cross Abstract: Post-harvest fruit quality assessment is essential for reducing food waste, yet reliable non-destructive methods typically depend on expensive hypersp

hardwarearxiv-cs-lg

S^2IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction

arXiv:2604.23296v1 Announce Type: cross Abstract: Aspect Sentiment Quad Prediction (ASQP) has seen significant advancements, largely driven by the powerful semantic understanding and generative capabi

local-aiarxiv-cs-ai

Hardware

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models

arXiv:2604.24708v1 Announce Type: cross Abstract: Training large neural networks with data-parallel stochastic gradient descent allocates N GPU replicas to compute effectively identical updates -- a p

hardwarearxiv-cs-ai

SWE-QA: Can Language Models Answer Repository-level Code Questions?

model-releasesarxiv-cs-cl

arXiv:2509.14635v2 Announce Type: replace Abstract: Understanding and reasoning about entire software repositories is an essential capability for intelligent software engineering tools. While existing

Zero-shot Large Language Models for Automatic Readability Assessment

arXiv:2604.24470v1 Announce Type: new Abstract: Unsupervised automatic readability assessment (ARA) methods have important practical and research applications (e.g., ensuring medical or educational ma

AromaGen: Interactive Generation of Rich Olfactory Experiences with Multimodal Language Models

model-releasesarxiv-cs-ai

arXiv:2604.01650v2 Announce Type: replace-cross Abstract: Smell's deep connection with food, memory, and social experience has long motivated researchers to bring olfaction into interactive systems. Y

27 Apr 2026

GenMatter: Perceiving Physical Objects with Generative Matter Models

arXiv:2604.22160v1 Announce Type: cross Abstract: Human visual perception offers valuable insights for understanding computational principles of motion-based scene interpretation. Humans robustly dete

local-aiarxiv-cs-ai

27 Apr 2026

HubRouter: A Pluggable Sub-Quadratic Routing Primitive for Hybrid Sequence Models

model-releasesarxiv-cs-lg

arXiv:2604.22442v1 Announce Type: new Abstract: We introduce HubRouter, a pluggable module that replaces O(n^2) attention layers with O(nM) hub-mediated routing, where M =20 shows increasing seed sens

27 Apr 2026

A Scale-Adaptive Framework for Joint Spatiotemporal Super-Resolution with Diffusion Models

arXiv:2604.21903v1 Announce Type: cross Abstract: Deep-learning video super-resolution has progressed rapidly, but climate applications typically super-resolve (increase resolution) either space or ti

researcharxiv-cs-ai

Multimodal Protein Language Models for Enzyme Kinetic Parameters: From Substrate Recognition to Conformational Adaptation

arXiv:2603.12845v2 Announce Type: replace Abstract: Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canon

safetyarxiv-cs-cv

Predicting Scale-Up of Metal-Organic Framework Syntheses with Large Language Models

arXiv:2604.20899v1 Announce Type: cross Abstract: Scalable synthesis remains the gate between MOF discovery and industrial deployment, as scale-up know-how is fragmented across disparate reports. We i

researcharxiv-cs-ai

Prototype-Based Test-Time Adaptation of Vision-Language Models

arXiv:2604.21360v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for vision-language models (VLMs) to bridge the distribution gap between pre-training and

Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom

model-releasesarxiv-cs-ai

arXiv:2604.19754v1 Announce Type: new Abstract: Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories p

Object Referring-Guided Scanpath Prediction with Perception-Enhanced Vision-Language Models

arXiv:2604.20361v1 Announce Type: new Abstract: Object Referring-guided Scanpath Prediction (ORSP) aims to predict the human attention scanpath when they search for a specific target object in a visua

ThermoQA: A Three-Tier Benchmark for Evaluating Thermodynamic Reasoning in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2604.19758v1 Announce Type: new Abstract: We present ThermoQA, a benchmark of 293 open-ended engineering thermodynamics problems in three tiers: property lookups (110 Q), component analysis (101

Tracing Relational Knowledge Recall in Large Language Models

arXiv:2604.19934v1 Announce Type: new Abstract: We study how large language models recall relational knowledge during text generation, with a focus on identifying latent representations suitable for r

Tutorials

A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions

arXiv:2604.17312v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a powerful post-training paradigm for enhancing the reasoning capabilities of large language models (LLMs). H

tutorialsarxiv-cs-lg

Applications

Compositional Steering of Large Language Models with Steering Tokens

arXiv:2601.05062v2 Announce Type: replace Abstract: Deploying LLMs in real-world applications requires controllable output that satisfies multiple desiderata at the same time. While existing work exte

applicationsarxiv-cs-cl

DeepThinkVLA: Enhancing Reasoning Capability of Vision-Language-Action Models

arXiv:2511.15669v2 Announce Type: replace Abstract: Does Chain-of-Thought (CoT) reasoning genuinely improve Vision-Language-Action (VLA) models, or does it merely add overhead? Existing CoT-VLA system

safetyarxiv-cs-lg

Defragmenting Language Models: An Interpretability-based Approach for Vocabulary Expansion

arXiv:2604.16656v1 Announce Type: new Abstract: All languages are equal; when it comes to tokenization, some are more equal than others. Tokens are the hidden currency that dictate the cost and latenc

emg2speech: Synthesizing speech from electromyography using self-supervised speech models

arXiv:2510.23969v2 Announce Type: replace-cross Abstract: We present a neuromuscular speech interface that translates electromyographic (EMG) signals recorded from orofacial muscles during speech arti

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users

model-releasesarxiv-cs-cl

arXiv:2603.16120v2 Announce Type: replace Abstract: Deep Research (DR) systems help researchers cope with ballooning publishing counts. Such tools synthesize scientific papers to answer research queri

LoReC: Rethinking Large Language Models for Graph Data Analysis

arXiv:2604.17897v1 Announce Type: new Abstract: The advent of Large Language Models (LLMs) has fundamentally reshaped the way we interact with graphs, giving rise to a new paradigm called GraphLLM. As

researcharxiv-cs-lg

Operationalizing Fairness in Text-to-Image Models: A Survey of Bias, Fairness Audits and Mitigation Strategies

arXiv:2604.16516v1 Announce Type: new Abstract: Text-to-Image (T2I) generation models have been widely adopted across various industries, yet are criticized for frequently exhibiting societal stereoty

safetyarxiv-cs-cv

SinkRouter: Sink-Aware Routing for Efficient Long-Context Decoding in Large Language and Multimodal Models

model-releasesarxiv-cs-lg

arXiv:2604.16883v1 Announce Type: new Abstract: In long-context decoding for LLMs and LMMs, attention becomes increasingly memory-bound because each decoding step must load a large amount of KV-cache

Target Parameterization in Diffusion Models for Nonlinear Spatiotemporal System Identification

arXiv:2604.17566v1 Announce Type: cross Abstract: Machine learning is becoming increasingly important for nonlinear system identification, including dynamical systems with spatially distributed output

researcharxiv-cs-lg

Follow the Flow: On Information Flow Across Textual Tokens in Text-to-Image Models

arXiv:2504.01137v3 Announce Type: replace Abstract: Text-to-image generation models suffer from alignment problems, where generated images fail to accurately capture the objects and relations in the t

safetyarxiv-cs-cl

20 Apr 2026

Prototype-Grounded Concept Models for Verifiable Concept Alignment

arXiv:2604.16076v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) aim to improve interpretability in Deep Learning by structuring predictions through human-understandable concepts, bu

safetyarxiv-cs-ai

20 Apr 2026

Where Do Vision-Language Models Fail? World Scale Analysis for Image Geolocalization

arXiv:2604.16248v1 Announce Type: new Abstract: Image geolocalization has traditionally been addressed through retrieval-based place recognition or geometry-based visual localization pipelines. Recent

local-aiarxiv-cs-cv

20 Apr 2026

Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models

arXiv:2508.15396v2 Announce Type: replace Abstract: The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a grow

Applications

Can Large Language Models Detect Methodological Flaws? Evidence from Gesture Recognition for UAV-Based Rescue Operation Based on Deep Learning

arXiv:2604.14161v1 Announce Type: new Abstract: Reliable evaluation is essential in machine learning research, yet methodological flaws-particularly data leakage-continue to undermine the validity of

applicationsarxiv-cs-cl

MapSR: Prompt-Driven Land Cover Map Super-Resolution via Vision Foundation Models

arXiv:2604.14582v1 Announce Type: new Abstract: High-resolution (HR) land-cover mapping is often constrained by the high cost of dense HR annotations. We revisit this problem from the perspective of m

MemGround: Long-Term Memory Evaluation Kit for Large Language Models in Gamified Scenarios

model-releasesarxiv-cs-cl

arXiv:2604.14158v1 Announce Type: new Abstract: Current evaluations of long-term memory in LLMs are fundamentally static. By fixating on simple retrieval and short-context inference, they neglect the

Agents

Numerical Instability and Chaos: Quantifying the Unpredictability of Large Language Models

arXiv:2604.13206v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into agentic workflows, their unpredictability stemming from numerical instability has eme

agentsarxiv-cs-lg

16 Apr 2026

Stochastic Trust-Region Methods for Over-parameterized Models

model-releasesarxiv-cs-lg

arXiv:2604.14017v1 Announce Type: cross Abstract: Under interpolation-type assumptions such as the strong growth condition, stochastic optimization methods can attain convergence rates comparable to f

16 Apr 2026

Agents

Training-Free Test-Time Contrastive Learning for Large Language Models

arXiv:2604.13552v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong reasoning capabilities, but their performance often degrades under distribution shift. Existing test-tim

agentsarxiv-cs-cl

16 Apr 2026

Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe

arXiv:2604.13016v1 Announce Type: cross Abstract: On-policy distillation (OPD) has become a core technique in the post-training of large language models, yet its training dynamics remain poorly unders

safetyarxiv-cs-ai

15 Apr 2026

A Progressive Training Strategy for Vision-Language Models to Counteract Spatio-Temporal Hallucinations in Embodied Reasoning

arXiv:2604.10506v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have made significant strides in static image understanding but continue to face critical hurdles in spatiotemporal reason

researcharxiv-cs-ai

Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models

arXiv:2604.10697v1 Announce Type: new Abstract: Large language models frequently exhibit hallucinations: fluent and confident outputs that are factually incorrect or unsupported by the input context.

Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models

arXiv:2604.10219v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoni

local-aiarxiv-cs-ai

GrOCE:Graph-Guided Online Concept Erasure for Text-to-Image Diffusion Models

arXiv:2511.12968v2 Announce Type: replace Abstract: Concept erasure aims to remove harmful, inappropriate, or copyrighted content from text-to-image diffusion models while preserving non-target semant

GTASA: Ground Truth Annotations for Spatiotemporal Analysis, Evaluation and Training of Video Models

arXiv:2604.10385v1 Announce Type: new Abstract: Generating complex multi-actor scenario videos remains difficult even for state-of-the-art neural generators, while evaluating them is hard due to the l

safetyarxiv-cs-cv

Mining Attribute Subspaces for Efficient Fine-tuning of 3D Foundation Models

arXiv:2604.10095v1 Announce Type: new Abstract: With the emergence of 3D foundation models, there is growing interest in fine-tuning them for downstream tasks, where LoRA is the dominant fine-tuning p

Agents

Physics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems

arXiv:2604.11807v1 Announce Type: cross Abstract: The stable operation of autonomous off-grid photovoltaic systems dictates reliance on solar forecasting algorithms that respect atmospheric thermodyna

agentsarxiv-cs-ai

Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference

arXiv:2604.11496v1 Announce Type: cross Abstract: Dual-encoder Vision-Language Models (VLMs) such as CLIP are often characterized as bag-of-words systems due to their poor performance on compositional

safetyarxiv-cs-cl

SVD-Prune: Training-Free Token Pruning For Efficient Vision-Language Models

arXiv:2604.11530v1 Announce Type: cross Abstract: Vision-Language Models (VLM) have revolutionized multimodal learning by jointly processing visual and textual information. Yet, they face significant

safetyarxiv-cs-ai