Search: “models”

From TF-IDF to Transformers: A Comparative and Ensemble Approach to Sentiment Classification

arXiv:2605.22003v1 Announce Type: new Abstract: Sentiment analysis, also referred to as opinion mining, primarily tries to extract opinion from any text-based data. In the context of movie reviews and

researcharxiv-cs-cl

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Model Releases

GHI: Graphormer over Conditioned Hypergraph Incidence for Aspect-Based Sentiment Analysis

DGX agent

arXiv:2605.22228v1 Announce Type: new Abstract: Aspect-based sentiment analysis (ABSA) requires models to bind sentiment evidence to the correct aspect, making it a natural testbed for fine-grained st

model-releasesarxiv-cs-cl

22 May 2026

H-Flow: Self-supervised Human Scene Flow via Physics-inspired Joint Multi-modal Learning

arXiv:2605.22629v1 Announce Type: new Abstract: Parametric human models capture global pose but cannot represent the non-rigid surface dynamics of clothing and soft tissue. Generic scene flow estimate

InteractScience: Programmatic and Visually-Grounded Evaluation of Interactive Scientific Demonstration Code Generation

arXiv:2510.09724v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly capable of generating complete applications from natural language instructions, creating new opp

Learning Spatiotemporal Sensitivity in Video LLMs via Counterfactual Reinforcement Learning

arXiv:2605.21988v1 Announce Type: new Abstract: Video large language models (Video LLMs) achieve strong benchmark accuracy, yet often answer video questions through shortcuts such as single-frame cues

LongVT: Incentivizing 'Thinking with Long Videos' via Native Tool Calling

arXiv:2511.20785v3 Announce Type: replace Abstract: Large multimodal models (LMMs) have shown great potential for video reasoning with textual Chain-of-Thought. However, they remain vulnerable to hall

M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

arXiv:2507.01053v4 Announce Type: replace-cross Abstract: Large-scale clinical databases offer opportunities for medical research, but their complexity creates barriers to effective use. The Medical I

MotiMotion: Motion-Controlled Video Generation with Visual Reasoning

arXiv:2605.22818v1 Announce Type: new Abstract: Current motion-controlled image-to-video generation models rigidly follow user-provided trajectories that are often sparse, imprecise, and causally inco

NuExtract3 released: open-weight 4B VLM for Markdown, OCR and structured extraction (self-hostable) [P]

model-releasesr-machinelearning

NuExtract3 is a unified 4B vision-language reasoning model for document understanding that combines structured information extraction with image-to-Markdown conversion, suitable for OCR and RAG prepro

oops! wild update, strongly supports @emollick’s overall take:

model-releasesgary-marcus--x

oops! wild update, strongly supports @emollick’s overall take: I have to eat crow on this, in light of further information. whatever OpenAI spent on Erdos using a new model, apparently you can get GPT

Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?

arXiv:2605.22109v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in human-facing roles where personality perception is critical, yet existing benchm

RAGCap-Bench: Benchmarking Capabilities of LLMs in Agentic Retrieval Augmented Generation Systems

arXiv:2510.13910v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) mitigates key limitations of Large Language Models (LLMs)-such as factual errors, outdated knowledge, and hallu

SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

arXiv:2512.10719v2 Announce Type: replace Abstract: End-to-end autonomous driving methods built on vision language models (VLMs) have undergone rapid development driven by their universal visual under

Tutorials

TextTeacher: What Can Language Teach About Images?

arXiv:2605.22098v1 Announce Type: new Abstract: The platonic representation hypothesis suggests that sufficiently large models converge to a shared representation geometry, even across modalities. Mot

tutorialsarxiv-cs-cv

Token-weighted Direct Preference Optimization with Attention

arXiv:2605.21883v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) aligns Large Language Models with human preferences without the need for a separate reward model. However, DPO trea

researcharxiv-cs-cl

VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis

arXiv:2605.22570v1 Announce Type: new Abstract: Spatio-temporal reasoning is a core capability for Multimodal Large Language Models (MLLMs) operating in the real world. As such, evaluating it precisel

We are making our discount permanent! 🎉 Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀

model-releasesjeremy-howard--x

DeepSeek has announced a permanent discount for its DeepSeek-V4-Pro model, encouraging developers to build and innovate with the platform. The announcement was made via social media and emphasizes the

When Cases Get Rare: A Retrieval Benchmark for Off-Guideline Clinical Question Answering

arXiv:2605.21807v1 Announce Type: new Abstract: Across medical specialties, clinical practice is anchored in evidence-based guidelines that codify best studied diagnostic and treatment pathways. These

A Free Lunch in LLM Compression: Revisiting Retraining after Pruning

arXiv:2510.14444v3 Announce Type: replace Abstract: Post-training pruning can substantially reduce LLM inference costs, but it often degrades quality unless the remaining weights are adapted. Since gl

Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations

arXiv:2602.19320v2 Announce Type: replace Abstract: Agentic memory systems enable large language model (LLM) agents to maintain state across long interactions, supporting long-horizon reasoning and pe

Break the context window barrier with Amazon Bedrock AgentCore

model-releasesaws-ml-blog

In this post, you will learn how to implement Recursive Language Models (RLM) using Amazon Bedrock AgentCore Code Interpreter and the Strands Agents SDK. By the end, you will know how to process docum

Can Conversational XAI Improve User Performance? An Experimental Study

arXiv:2605.20439v1 Announce Type: new Abstract: Explainable AI (XAI) techniques aim to provide insights into predictive models and enhance user performance, yet they often fall short of these expectat

researcharxiv-cs-lg

Causal Path Alignment: Anchoring the Optimization Trajectory for Controllable In-Parameter Knowledge Editing

arXiv:2506.04042v2 Announce Type: replace Abstract: Knowledge editing is pivotal for efficiently updating the parametric memory of Large Language Models (LLMs), enabling them to function as evolving a

Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.…

model-releasesfireworks-ai--x

Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer

Dynamic Video Generation: Shaping Video Generation Across Time and Space

arXiv:2605.21042v1 Announce Type: new Abstract: Diffusion models have achieved impressive performance in video generation, but their iterative denoising process remains computationally expensive due t

Exploring Deep Learning and Ultra-Widefield Imaging for Diabetic Retinopathy and Macular Edema

arXiv:2603.08235v2 Announce Type: replace Abstract: Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of preventable blindness among working-age adults. Traditional approac

Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy

arXiv:2605.20965v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have shown remarkable performance on a wide range of vision-language tasks. Despite this progress, they are still p

FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents

arXiv:2603.01712v2 Announce Type: replace-cross Abstract: Fine-tuning large language models for vertical domains remains labor-intensive, requiring practitioners to curate data, configure training, an

How Much Online RL is Enough? Informative Rollouts for Offline Preference Optimization in RLVR

arXiv:2605.21266v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a powerful paradigm for reasoning in language models, with GRPO as its primary exam

Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory

arXiv:2602.06025v2 Announce Type: replace Abstract: Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offl

Local Ai

LoCar: Localization-Aware Evaluation of In-Vehicle Assistants through Fine-Grained Sociolinguistic Control

arXiv:2605.21086v1 Announce Type: new Abstract: While Large Language Models (LLMs) are increasingly integrated into in-vehicle conversational systems, identifying the optimal model remains challenging

local-aiarxiv-cs-cl

Mechanics of Bias and Reasoning: Interpreting the Impact of Chain-of-Thought Prompting on Gender Bias in LLMs

arXiv:2605.20410v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in socially sensitive settings despite substantial documentation that they encode gender biases.

Safety

Mechanistic Interpretability for Learning Assurance of a Vision-Based Landing System

arXiv:2605.20607v1 Announce Type: cross Abstract: EASA's learning-assurance guidance requires data-driven aviation systems to build and monitor their own situation representation, yet for neural netwo

safetyarxiv-cs-cv

PGC: Peak-Guided Calibration for Generalizable AI-Generated Image Detection

arXiv:2605.21207v1 Announce Type: new Abstract: The rapid evolution of generative AI, from GANs to modern diffusion models, has resulted in increasingly subtle discriminative clues. These fine-grained

QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs

arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res

RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution

arXiv:2605.21195v1 Announce Type: new Abstract: Discrete autoregressive (AR) text-to-image (T2I) models pair a VQ tokenizer with an AR policy, and current post-training pipelines optimize only the pol

Refining and Reusing Annotation Guidelines for LLM Annotation

arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized convention

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation

arXiv:2605.20189v1 Announce Type: cross Abstract: Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with prima

Local Ai

Sustainability Is Not Linear: Quantifying Performance, Energy, and Privacy Trade-offs in On-Device Intelligence

arXiv:2603.26603v2 Announce Type: replace-cross Abstract: The migration of Large Language Models (LLMs) from cloud clusters to edge devices promises enhanced privacy and offline accessibility, but thi

local-aiarxiv-cs-lg

TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design

arXiv:2605.20731v1 Announce Type: new Abstract: Text-to-image models produce graphic design at production scale, but their supervision comes from photo-style preference data with a single overall verd

Terminal-World: Scaling Terminal-Agent Environments via Agent Skills

arXiv:2605.20876v1 Announce Type: new Abstract: Terminal agents extend Large Language Models with the ability to execute tasks directly in command-line environments, but their progress is bottlenecked

TreeText-CTS: Compact, Source-Traceable Tree-Path Evidence for Irregular Clinical Time-Series Prediction

arXiv:2605.20292v1 Announce Type: new Abstract: Numerical time-series models can effectively process irregular electronic health record (EHR) trajectories, but they do not naturally expose the measure

researcharxiv-cs-lg

Safety

What Semantics Survive the Connector? Diagnosing VLM-to-DiT Alignment in Video Editing

arXiv:2605.20795v1 Announce Type: new Abstract: Flow matching based video generative models have been increasingly relying on prepended Vision-Language Models (VLMs) to handle complex, instruction-bas

safetyarxiv-cs-cv

A Bitter Lesson for Data Filtering

arXiv:2605.19407v1 Announce Type: cross Abstract: We investigate data filtering for large model pretraining via new scaling studies that target the high compute, data-scarce regime. In spite of an app

A Reproducibility Analysis of PO4ISR: Diagnosing and Mitigating Semantic Drift in LLM-Based Session Recommendation

arXiv:2605.18780v1 Announce Type: cross Abstract: Reasoning-based Large Language Models (LLMs) like PO4ISR have set new benchmarks in session-based recommendation. However, the reproducibility of thei

Aero-World: Action-Conditioned Aerial Video Generation from Inertial Controls

arXiv:2605.19728v1 Announce Type: new Abstract: Foundation video models produce visually impressive results, but their use in embodied AI remains limited because they are primarily trained on natural

Agents

AQuaUI: Visual Token Reduction for GUI Agents with Adaptive Quadtrees

arXiv:2605.19260v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently emerged as promising backbones for GUI-agent models, where high-resolution GUI screenshots are introduced t

agentsarxiv-cs-ai

Block-Based Double Decoders

arXiv:2605.18807v1 Announce Type: cross Abstract: Encoder-decoder models offer substantial inference-time savings over decoder-only models, but their pretraining objectives suffer from sparse supervis

researcharxiv-cs-ai