Search: “models”

LLM-AUG: Robust Wireless Data Augmentation with In-Context Learning in Large Language Models

arXiv:2604.17770v1 Announce Type: new Abstract: Data scarcity remains a fundamental bottleneck in applying deep learning to wireless communication problems, particularly in scenarios where collecting

researcharxiv-cs-lg

Model Releases

Low-rank Orthogonalization for Large-scale Matrix Optimization with Applications to Foundation Model Training

DGX agent

arXiv:2509.11983v2 Announce Type: replace Abstract: Neural network (NN) training is inherently a large-scale matrix optimization problem, yet the matrix structure of NN parameters has long been overlo

model-releasesarxiv-cs-lg

21 Apr 2026

Industry

Mastering the 600B+ Frontier: Optimizing Large Model Deployments on the Inference Cloud

This DigitalOcean guide covers strategies and best practices for deploying and optimizing very large language models (600 billion+ parameters) on cloud infrastructure, focusing on inference performanc

industrydigitalocean

MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning

arXiv:2604.16929v1 Announce Type: new Abstract: The accurate extraction of scientific measurements from literature is a critical yet challenging task in AI4Science, enabling large-scale analysis and i

MHSafeEval: Role-Aware Interaction-Level Evaluation of Mental Health Safety in Large Language Models

arXiv:2604.17730v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored as scalable tools for mental health counseling, yet evaluating their safety remains challenging d

Applications

Modeling Human Perspectives with Socio-Demographic Representations

arXiv:2604.18069v1 Announce Type: new Abstract: Humans often hold different perspectives on the same issues. In many NLP tasks, annotation disagreement can reflect valid subjective perspectives. Model

applicationsarxiv-cs-cl

Modeling Multiple Support Strategies within a Single Turn for Emotional Support Conversations

arXiv:2604.17972v1 Announce Type: new Abstract: Emotional Support Conversation (ESC) aims to assist individuals experiencing distress by generating empathetic and supportive dialogue. While prior work

Applications

NaviFormer: A Deep Reinforcement Learning Transformer-like Model to Holistically Solve the Navigation Problem

arXiv:2604.16967v1 Announce Type: new Abstract: Path planning is usually solved by addressing either the (high-level) route planning problem (waypoint sequencing to achieve the final goal) or the (low

applicationsarxiv-cs-ro

Tutorials

Neural Garbage Collection: Learning to Forget while Learning to Reason

arXiv:2604.18002v1 Announce Type: new Abstract: Chain-of-thought reasoning has driven striking advances in language model capability, yet every reasoning step grows the KV cache, creating a bottleneck

tutorialsarxiv-cs-lg

On Different Notions of Redundancy in Conditional-Independence-Based Discovery of Graphical Models

arXiv:2502.08531v3 Announce Type: replace Abstract: Conditional-independence-based discovery uses statistical tests to identify a graphical model that represents the independence structure of variable

researcharxiv-cs-lg

On the Interpolation Effect of Score Smoothing in Diffusion Models

arXiv:2502.19499v3 Announce Type: replace Abstract: Diffusion models have achieved remarkable progress in various domains with an intriguing ability to produce new data that do not exist in the traini

researcharxiv-cs-lg

Precise Debugging Benchmark: Is Your Model Debugging or Regenerating?

arXiv:2604.17338v1 Announce Type: cross Abstract: Unlike code completion, debugging requires localizing faults and applying targeted edits. We observe that frontier LLMs often regenerate correct but o

Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models

arXiv:2604.17415v1 Announce Type: cross Abstract: Reward-based fine-tuning aims to steer a pretrained diffusion or flow-based generative model toward higher-reward samples while remaining close to the

safetyarxiv-cs-cv

SafeLM: Unified Privacy-Aware Optimization for Trustworthy Federated Large Language Models

arXiv:2604.16606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains, yet a unified treatment of their overlapping safety challenges remains

safetyarxiv-cs-lg

Safety, Security, and Cognitive Risks in State-Space Models: A Systematic Threat Analysis with Spectral, Stateful, and Capacity Attacks

arXiv:2604.16424v1 Announce Type: cross Abstract: State-Space Models (SSMs) -- structured SSMs (S4, S4D, DSS, S5), selective SSMs (Mamba, Mamba-2), and hybrid architectures (Jamba) -- are deployed in

Sparse Feature Coactivation Reveals Causal Semantic Modules in Large Language Models

arXiv:2506.18141v3 Announce Type: replace Abstract: We identify semantically coherent, context-consistent network components in large language models (LLMs) using coactivation of sparse autoencoder (S

StageMem: Lifecycle-Managed Memory for Language Models

arXiv:2604.16774v1 Announce Type: new Abstract: Long-horizon language model systems increasingly rely on persistent memory, yet many current designs still treat memory primarily as a static store: wri

Synthetic Data Generation for Training Diversified Commonsense Reasoning Models

arXiv:2603.18361v2 Announce Type: replace Abstract: Conversational agents are required to respond to their users not only with high quality (i.e. commonsense bearing) responses, but also considering m

Tools

True to form, I've already seen OpenAI themselves refer to the new image model as 'ChatGPT Images 2.0', 'Image gen 2' and 'gpt-image-2'

OpenAI has been using multiple informal names internally and externally for its new image generation model, including 'ChatGPT Images 2.0,' 'Image gen 2,' and 'gpt-image-2.' The post highlights incons

toolssimon-willison--x

VIBE: Voice-Induced open-ended Bias Evaluation for Large Audio-Language Models via Real-World Speech

arXiv:2604.17248v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) are increasingly integrated into daily applications, yet their generative biases remain underexplored. Existing sp

When Earth Foundation Models Meet Diffusion: An Application to Land Surface Temperature Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2604.16841v1 Announce Type: new Abstract: Land surface temperature (LST) super-resolution is important for environmental monitoring. However, it remains challenging as coarse thermal observation

When Visuals Aren't the Problem: Evaluating Vision-Language Models on Misleading Data Visualizations

model-releasesarxiv-cs-cv

arXiv:2603.22368v2 Announce Type: replace Abstract: Visualizations help communicate data insights, but deceptive data representations can distort their interpretation and propagate misinformation. Whi

XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments

arXiv:2604.18484v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex

agentsarxiv-cs-cv

A Systematic Study of Training-Free Methods for Trustworthy Large Language Models

arXiv:2604.15789v1 Announce Type: new Abstract: As Large Language Models (LLMs) receive increasing attention and are being deployed across various domains, their potential risks, including generating

Local Ai

Adapting in the Dark: Efficient and Stable Test-Time Adaptation for Black-Box Models

arXiv:2604.15609v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) for black-box models accessible only via APIs remains a largely unexplored challenge. Existing approaches such as post-hoc

local-aiarxiv-cs-cv

Industry

Anthropic's Mythos AI model sparks fears of turbocharged hacking

Anthropic announced its Mythos AI model on April 7 and refused to release it publicly, citing its unprecedented ability to find and exploit software vulnerabilities . The company is instead limiting a

industryars-technica

Characterising LLM-Generated Competency Questions: a Cross-Domain Empirical Study using Open and Closed Models

arXiv:2604.16258v1 Announce Type: new Abstract: Competency Questions (CQs) are a cornerstone of requirement elicitation in ontology engineering. CQs represent requirements as a set of natural language

CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling

arXiv:2602.01766v2 Announce Type: replace-cross Abstract: The quadratic complexity and indefinitely growing key-value (KV) cache of standard Transformers pose a major barrier to long-context processin

DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition

arXiv:2604.15866v1 Announce Type: cross Abstract: Large language models (LLMs) have advanced information extraction (IE) by enabling zero-shot and few-shot named entity recognition (NER), yet their ge

EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence

arXiv:2509.14977v2 Announce Type: replace Abstract: Ultrasound imaging has become the preferred imaging modality for early cancer screening due to its advantages of non-ionizing radiation, low cost, a

researcharxiv-cs-cv

Tools

Kimi has been the most popular model on Fireworks, both out of the box and as a fine-tuning base (including Composer 2) Now Kimi K2.6 is liv…

Kimi has been the most popular model on Fireworks, both out of the box and as a fine-tuning base (including Composer 2) Now Kimi K2.6 is live with huge jumps (10+%) in coding, long-running agents and

toolsfireworks-ai--x

KWBench: Measuring Unprompted Problem Recognition in Knowledge Work

arXiv:2604.15760v1 Announce Type: new Abstract: We introduce the first version of KWBench (Knowledge Work Bench), a benchmark for unprompted problem recognition in large language models: can an LLM id

Large Language Models for Market Research: A Data-augmentation Approach

arXiv:2412.19363v3 Announce Type: replace Abstract: Large Language Models (LLMs) have transformed artificial intelligence by excelling in complex natural language processing tasks. Their ability to ge

safetyarxiv-cs-ai

Large Reasoning Models Are (Not Yet) Multilingual Latent Reasoners

arXiv:2601.02996v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve strong performance on mathematical reasoning tasks, often attributed to their capability to generate explicit

literally my basic model since 1998. crazy that some people still haven’t figured this out.

literally my basic model since 1998. crazy that some people still haven’t figured this out. My basic model of capabilities: LLMs are good at problems similar to those that appear in their training dat

safetygary-marcus--x

Applications

Modeling of ASD/TD Children's Behaviors in Interaction with a Virtual Social Robot During a Music Education Program Using Deep Neural Networks

arXiv:2604.15314v1 Announce Type: cross Abstract: This research aimed to develop an intelligent system to evaluate performance and extract behavioral models for children with ASD and neurotypical (TD)

applicationsarxiv-cs-ai

Nice paper combining the strength of Skills and RAG. Most RAG systems retrieve on every query, whether the model needs help or not. This is …

Nice paper combining the strength of Skills and RAG. Most RAG systems retrieve on every query, whether the model needs help or not. This is wasteful when the model already knows the answer, and often

agentsdair-ai--x

Olmo Hybrid: From Theory to Practice and Back

arXiv:2604.03444v3 Announce Type: replace-cross Abstract: Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid m

Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research

arXiv:2412.04497v5 Announce Type: replace-cross Abstract: Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite the

researcharxiv-cs-ai

opus 4.7 dropped last week with two new features: xhigh effort: more compute when you need it task budgets: the model knows its limit and wr…

opus 4.7 dropped last week with two new features: xhigh effort: more compute when you need it task budgets: the model knows its limit and wraps up gracefully, this is a great example of giving the mod

agentsharrison-chase--x

Tools

Our researchers are heading to ICLR with new work: model efficiency, long-context reasoning, next-gen attention and decoding, and more. Chec…

Our researchers are heading to ICLR with new work: model efficiency, long-context reasoning, next-gen attention and decoding, and more. Check out what we've been building 👇🏼 #TogetherResearch #AINativ

toolstogether-ai--x

OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction

model-releasesarxiv-cs-lg

arXiv:2512.06987v2 Announce Type: replace Abstract: Accurately predicting experimentally realizable 3D molecular crystal structures from their 2D chemical graphs is a long-standing open challenge in c

{pi}_{0.7}: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

arXiv:2604.15483v1 Announce Type: new Abstract: We present a new robotic foundation model, called {pi}_{0.7}, that can enable strong out-of-the-box performance in a wide range of scenarios. {pi}_{0.7}

agentsarxiv-cs-lg

PixDLM: A Dual-Path Multimodal Language Model for UAV Reasoning Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.15670v1 Announce Type: new Abstract: Reasoning segmentation has recently expanded from ground-level scenes to remote-sensing imagery, yet UAV data poses distinct challenges, including obliq

Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs

arXiv:2604.15780v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in real-world applications, but even aligned models such as Mistral and LLaVA still exhibit unsafe b

Reward Weighted Classifier-Free Guidance as Policy Improvement in Autoregressive Models

arXiv:2604.15577v1 Announce Type: cross Abstract: Consider an auto-regressive model that produces outputs x (e.g., answers to questions, molecules) each of which can be summarized by an attribute vect

safetyarxiv-cs-ai

Scalable spatial point process models for forensic footwear analysis

arXiv:2602.07006v2 Announce Type: replace Abstract: Shoe print evidence recovered from crime scenes plays a key role in forensic investigations. By examining shoe prints, investigators can determine d

researcharxiv-cs-cv

SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos

arXiv:2602.05638v3 Announce Type: replace Abstract: While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that w

researcharxiv-cs-cv