Search: “model-releases”

Cloud-hosted models will become more niche/seldom-used as much cheaper local models fulfill that which 90% of consumers need from AI. Lots o…

Cloud-hosted models will become more niche/seldom-used as much cheaper local models fulfill that which 90% of consumers need from AI. Lots of models to buy/use, but very few hardware options upon whic

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CLT-Optimal Parameter Error Bounds for Linear System Identification

arXiv:2604.21270v1 Announce Type: cross Abstract: There has been remarkable progress over the past decade in establishing finite-sample, non-asymptotic bounds on recovering unknown system parameters f

Cognitive Amplification vs Cognitive Delegation in Human-AI Systems: A Metric Framework

arXiv:2603.18677v2 Announce Type: replace-cross Abstract: Artificial intelligence is increasingly embedded in human decision making. In some cases, it enhances human reasoning. In others, it fosters e

come to the most ai pilled country per capita @anthropicai we want u

This post from Swyx appears to be a humorous or provocative invitation directed at Anthropic AI, suggesting a particular country has the highest per-capita adoption or focus on AI technology and encou

model-releasesswyx--x

Compliance Moral Hazard and the Backfiring Mandate

arXiv:2604.21789v1 Announce Type: cross Abstract: Competing firms that serve shared customer populations face a fundamental information aggregation problem: each firm holds fragmented signals about ri

Concurrence: A dependence criterion for time series, applied to biological data

arXiv:2512.16001v2 Announce Type: replace-cross Abstract: Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often ex

Congrats to @deepseek_ai team! Doing the numbers I would estimate: Pro < 14m for the final training run Flash < 4m Ratio of active params …

model-releasesemad-mostaque--x

Congrats to @deepseek_ai team! Doing the numbers I would estimate: Pro < 14m for the final training run Flash < 4m Ratio of active params x total training tokens vs v3 Total compute costs (data prep,

Context Is What You Need: The Maximum Effective Context Window for Real World Limits of LLMs

arXiv:2509.21361v2 Announce Type: replace-cross Abstract: Large language model (LLM) providers boast big numbers for maximum context window sizes. To test the real world use of context windows, we 1)

CorridorVLA: Explicit Spatial Constraints for Generative Action Heads via Sparse Anchors

arXiv:2604.21241v1 Announce Type: cross Abstract: Vision--Language--Action (VLA) models often use intermediate representations to connect multimodal inputs with continuous control, yet spatial guidanc

Counterfactual Segmentation Reasoning: Diagnosing and Mitigating Pixel-Grounding Hallucination

arXiv:2506.21546v4 Announce Type: replace-cross Abstract: Segmentation Vision-Language Models (VLMs) have significantly advanced grounded visual understanding, yet they remain prone to pixel-grounding

Cross-Entropy Is Load-Bearing: A Pre-Registered Scope Test of the K-Way Energy Probe on Bidirectional Predictive Coding

arXiv:2604.21286v1 Announce Type: cross Abstract: Cacioli (2026) showed that the K-way energy probe on standard discriminative predictive coding networks reduces approximately to a monotone function o

Cross-Session Threats in AI Agents: Benchmark, Evaluation, and Algorithms

arXiv:2604.21131v1 Announce Type: cross Abstract: AI-agent guardrails are memoryless: each message is judged in isolation, so an adversary who spreads a single attack across dozens of sessions slips p

CSC: Turning the Adversary's Poison against Itself

arXiv:2604.21416v1 Announce Type: cross Abstract: Poisoning-based backdoor attacks pose significant threats to deep neural networks by embedding triggers in training data, causing models to misclassif

Data-Driven Open-Loop Simulation for Digital-Twin Operator Decision Support in Wastewater Treatment

arXiv:2604.20935v1 Announce Type: cross Abstract: Wastewater treatment plants (WWTPs) need digital-twin-style decision support tools that can simulate plant response under prescribed control plans, to

DAVIS: OOD Detection via Dominant Activations and Variance for Increased Separation

model-releasesarxiv-cs-cv

arXiv:2601.22703v2 Announce Type: replace Abstract: Detecting out-of-distribution (OOD) inputs is a critical safeguard for deploying machine learning models in the real world. However, most post-hoc d

🎉 Day-0 support for @deepseek_ai V4 Pro and Flash on vLLM — a new generation of DeepSeek model, purpose-built for tasks up to 1M tokens. Al…

model-releasesdylan-patel--x

🎉 Day-0 support for @deepseek_ai V4 Pro and Flash on vLLM — a new generation of DeepSeek model, purpose-built for tasks up to 1M tokens. Alongside the release, we're publishing a first-principles walk

Decoupled DiLoCo for Resilient Distributed Pre-training

model-releasesarxiv-cs-cl

arXiv:2604.21428v1 Announce Type: new Abstract: Modern large-scale language model pre-training relies heavily on the single program multiple data (SPMD) paradigm, which requires tight coupling across

Deep FinResearch Bench: Evaluating AI's Ability to Conduct Professional Financial Investment Research

arXiv:2604.21006v1 Announce Type: new Abstract: We introduce Deep FinResearch Bench, a practical and comprehensive evaluation framework for deep research (DR) agents in financial investment research.

DeepSeek open-sources V4 large language model series

model-releasessiliconangle

Chinese artificial intelligence developer DeepSeek today released a new series of open-source large language models. V4, as the algorithm family is called, comprises two LLMs on launch. There’s the fl

DeepSeek releases its new flagship models V4 Pro and V4 Flash in preview, saying V4 Pro trails the performance of state-of-the-art models by about 3 to 6 months (Bloomberg)

Bloomberg: DeepSeek releases its new flagship models V4 Pro and V4 Flash in preview, saying V4 Pro trails the performance of state-of-the-art models by about 3 to 6 months — DeepSeek rolled out previe

DeepSeek V4 - almost on the frontier, a fraction of the price

model-releasessimon-willison

Chinese AI lab DeepSeek's last model release was V3.2 (and V3.2 Speciale) last December. They just dropped the first of their hotly anticipated V4 series in the shape of two preview models, DeepSeek-V

DeepSeek-V4: a million-token context that agents can actually use

model-releaseshugging-face

DeepSeek-V4 is an advanced language model featuring a million-token context window that enables practical agentic applications beyond simple retrieval. The model demonstrates improved efficiency and u

DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernel…

model-releasesdylan-patel--x

DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernels. We also deliver a verified RL training pipeline in Miles

deepseek-v4-flash is now available on Ollama's cloud! Hosted in the US. Try it with Claude Code: ollama launch claude --model deepseek-v4-fl…

deepseek-v4-flash is now available on Ollama's cloud! Hosted in the US. Try it with Claude Code: ollama launch claude --model deepseek-v4-flash:cloud Try it with OpenClaw: ollama launch openclaw --mod

model-releasesollama--x

DEEPSEEK-V4 IS RELEASED

DeepSeek-V4 is a newly released AI model announced by Clem Delangue on X (formerly Twitter). The release likely represents an updated version of the DeepSeek model series with improvements in capabili

DeepSeek v4 just dropped

DeepSeek has released v4, its latest model iteration. The announcement was made by Clem Delangue on X (formerly Twitter). This likely represents a significant update to DeepSeek's AI capabilities, tho

DeepSeek-V4 just dropped on Hugging Face https://huggingface.co/collections/deepseek-ai/deepseek-v4

DeepSeek-V4, a new model release from DeepSeek AI, has been made available on Hugging Face's model hub. The release was announced by Clem Delangue and includes model weights and resources accessible t

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 DeepSeek-V4-Pro: 1.6T t…

model-releasesjeremy-howard--x

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top

Deepseek v4 Pro

DeepSeek-V4-Pro is a Mixture-of-Experts language model with 1.6 trillion total parameters and 49 billion activated per token, supporting a 1 million token context length. Released under the MIT Licens

model-releasesr-ollama

DeepSeek V4 Pro costs 1.74/1M input tokens and 3.48/1M output tokens, while V4 Flash costs 0.14/1M and 0.28/1M; both models are the cheapest in their class (Simon Willison/Simon Willison's Weblog)

Simon Willison / Simon Willison's Weblog: DeepSeek V4 Pro costs 1.74/1M input tokens and 3.48/1M output tokens, while V4 Flash costs 0.14/1M and 0.28/1M; both models are the cheapest in their class —

DeepSeek V4 Pro has 1.6T total parameters, its largest model by the metric, and V4 Flash has 284B parameters; both models have a context window of 1M tokens (Vincent Chow/South China Morning Post)

Vincent Chow / South China Morning Post: DeepSeek V4 Pro has 1.6T total parameters, its largest model by the metric, and V4 Flash has 284B parameters; both models have a context window of 1M tokens —

DeepSeek V4 Pro is now available on Together AI. DeepSeek V4 Flash coming soon. Try it now: http://www.together.ai/models/deepseek-v4-pro#

model-releasestogether-ai--x

DeepSeek V4 Pro is now available through Together AI's model platform, with the faster DeepSeek V4 Flash variant expected to launch soon. Together AI is offering users the ability to access and test D

DenoiseRank: Learning to Rank by Diffusion Models

arXiv:2604.20852v1 Announce Type: cross Abstract: Learning to rank (LTR) is one of the core tasks in Machine Learning. Traditional LTR models have made great progress, but nearly all of them are imple

Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles

arXiv:2604.21152v1 Announce Type: cross Abstract: As state-of-the-art Large Language Models (LLMs) have become ubiquitous, ensuring equitable performance across diverse demographics is critical. Howev

Differentially Private Model Merging

arXiv:2604.20985v1 Announce Type: cross Abstract: In machine learning applications, privacy requirements during inference or deployment time could change constantly due to varying policies, regulation

Diplomatic cable: US State Department has ordered a global push to bring attention to what it says are efforts by Chinese companies to steal IP from US AI labs (Raphael Satter/Reuters)

Raphael Satter / Reuters: Diplomatic cable: US State Department has ordered a global push to bring attention to what it says are efforts by Chinese companies to steal IP from US AI labs — The U.S. Sta

Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models

model-releasesarxiv-cs-cl

arXiv:2507.04023v3 Announce Type: replace Abstract: Large language models (LLMs) achieve impressive performance on complex mathematical benchmarks yet sometimes fail on basic math reasoning while gene

Do MLLMs Understand Pointing? Benchmarking and Enhancing Referential Reasoning in Egocentric Vision

model-releasesarxiv-cs-cv

arXiv:2604.21461v1 Announce Type: new Abstract: Egocentric AI agents, such as smart glasses, rely on pointing gestures to resolve referential ambiguities in natural language commands. However, despite

Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis

arXiv:2604.20928v1 Announce Type: cross Abstract: Fault diagnosis under unseen operating conditions remains highly challenging when labeled data are scarce. Semi-supervised domain generalization fault

Dr. Assistant: Enhancing Clinical Diagnostic Inquiry via Structured Diagnostic Reasoning Data and Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2601.13690v2 Announce Type: replace Abstract: Clinical Decision Support Systems (CDSSs) provide reasoning and inquiry guidance for physicians, yet they face notable challenges, including high ma

Droplet-LNO: Physics-Informed Laplace Neural Operators for Accurate Prediction of Droplet Spreading Dynamics on Complex Surfaces

arXiv:2604.20993v1 Announce Type: new Abstract: Spreading of liquid droplets on solid substrates constitutes a classic multiphysics problem with widespread applications ranging from inkjet printing, s

Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms

arXiv:2604.21473v1 Announce Type: cross Abstract: In the treatment of complex diseases, treatment regimens using a single drug often yield limited efficacy and can lead to drug resistance. In contrast

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization

arXiv:2411.00171v2 Announce Type: replace Abstract: To avoid myopic behavior, multi-step lookahead Bayesian optimization (BO) algorithms consider the sequential nature of BO and have demonstrated prom

Efficient Multi-Source Knowledge Transfer by Model Merging

model-releasesarxiv-cs-cv

arXiv:2508.19353v2 Announce Type: replace-cross Abstract: While transfer learning is an effective strategy, it often overlooks the opportunity to leverage knowledge from numerous available models onli

Empirical Comparison of Agent Communication Protocols for Task Orchestration

arXiv:2603.22823v3 Announce Type: replace Abstract: Context. The problem of comparative evaluation of communication protocols for task orchestration by large language model (LLM) agents is considered.

EngramaBench: Evaluating Long-Term Conversational Memory with Structured Graph Retrieval

arXiv:2604.21229v1 Announce Type: cross Abstract: Large language model assistants are increasingly expected to retain and reason over information accumulated across many sessions. We introduce Engrama

Enhancing Science Classroom Discourse Analysis through Joint Multi-Task Learning for Reasoning-Component Classification

arXiv:2604.21137v1 Announce Type: cross Abstract: Analyzing the reasoning patterns of students in science classrooms is critical for understanding knowledge construction mechanism and improving instru

Evaluating AI Meeting Summaries with a Reusable Cross-Domain Pipeline

arXiv:2604.21345v1 Announce Type: new Abstract: We present a reusable evaluation pipeline for generative AI applications, instantiated for AI meeting summaries and released with a public artifact pack