Search: “model-releases”

Broken Image Generator v2.0

Does anyone have an idea, when OpenAI will fix ChatGPT's glitched images? Since the 2.0 image generator was released, there is ugly glitches when you use generated image as a reference or just change

model-releasesr-chatgpt

BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning

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DGX agent

arXiv:2607.29302v1 Announce Type: cross Abstract: Reliable robot learning requires a world simulator that can predict action consequences before execution on physical hardware, including risky and fai

model-releasesarxiv-cs-cv

3 Aug 2026

CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models

arXiv:2607.28991v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inp

Can AI Evaluate AI Scientists? A Benchmarking Study of Autonomous Research Generation Systems Using Automated Multi-Model Review

arXiv:2607.28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery. However, evaluating and compari

Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery

arXiv:2603.03322v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated remarkable potential in automatic knowledge discovery. However, rig

Can LLMs Really Understand Item Difficulty Levels? Implications for Automated Item Generation Using LLMs

model-releasesarxiv-cs-cl

arXiv:2607.28634v1 Announce Type: new Abstract: The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments. This study explores h

Cato Networks launches Agentic Threat Prevention to counter AI-assisted attacks

model-releasessiliconangle

Networking and security company Cato Networks Ltd. today introduced Cato Agentic Threat Prevention, a capability that uses autonomous agents to predict the route an attacker is likely to take through

CBCT-IQ: A Publicly Available Annotated Cone-Beam CT Dataset for Image Quality Assessment and Benchmarking

arXiv:2607.29253v1 Announce Type: cross Abstract: Medical image quality plays a critical role in diagnostic accuracy, especially in X-ray-based imaging modalities such as cone-beam computed tomography

China’s Alibaba takes another swipe at America’s AI supremacy

model-releasesthe-verge-ai

Chinese tech giant Alibaba released what it says is its largest and 'most capable AI model to date,' claiming performance rivaling the best systems from US frontier labs Anthropic and OpenAI, as well

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.11885v2 Announce Type: replace Abstract: Diffusion-based policies generalize poorly in semantic manipulation, a key obstacle to real-world deployment, because text-only instructions cannot

CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning

arXiv:2607.29172v1 Announce Type: cross Abstract: While robot foundation models are growing increasingly capable, the strongest models are typically trained on proprietary data and remain closed-sourc

CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents

arXiv:2607.19338v2 Announce Type: replace Abstract: Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect an

Combining Large Language Models and Symbolic Reasoning for Multi-Robot Temporal Planning through Explainable Knowledge Bases

arXiv:2502.19135v2 Announce Type: replace Abstract: We present PLANTOR, a framework for generating and executing multi-robot task plans from natural-language task descriptions through LLM-assisted kno

Communication-Efficient Secure Aggregation in Decentralized Learning

arXiv:2405.07708v3 Announce Type: replace Abstract: Decentralized learning (DL) enables participants to collaboratively train models without a central server, yet it faces significant scalability chal

Cortex Framework v7 is GA: Build agentic workflows without disrupting SAP operations

model-releasesgoogle-cloud-ai

Businesses want to quickly and safely deploy AI agents to drive revenue, mitigate risk, and optimize capital, all without disrupting mission-critical ERP systems. And to power AI agents, you need more

COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention

arXiv:2607.28649v1 Announce Type: cross Abstract: COSI-Lab presents a multimodal, multi-sensor dataset of an interdisciplinary scientific workshop containing 32 academics at an international conferenc

CrowdStrike finds AI systems under direct attack as exploit windows shrink

model-releasessiliconangle

Artificial intelligence has become a target for attackers rather than only a tool they use, according to CrowdStrike Holdings Inc.’s “2026 Threat Hunting Report,” released today. The annual report dra

Curriculum Matters: Data-Efficient Relational PFN Pretraining with Synthetic Data

arXiv:2607.29120v1 Announce Type: new Abstract: Relational Prior-Data Fitted Networks (PFNs) such as RDB-PFN approximate Bayesian inference over multi-table relational databases by pretraining on mill

DART: Dual-Axis Airborne Reachability-Gated Torque-Reaction for Off-Road Vehicle Jumps

model-releasesarxiv-cs-ro

arXiv:2607.29011v1 Announce Type: new Abstract: Traversing crests, ledges, and ditches at high speed often launches vehicles into the air, and a mishandled landing presents a substantial crash hazard.

DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation

arXiv:2607.29078v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models on their own rollouts to reduce exposure bias. However, in multi-turn agent scenarios, early student

'Data center in a Box (on Wheels)' 256Gb VRAM/512Gb RAM AI Server 6-8 Month Operational Review, Stability Write Up, Benchmarks

I've been out of these forums for awhile but I figured I would provide a formal update on how this has been going now that it has some operation time under its belt, just to put the information out th

Data Turnstile: A Scalable Open Framework for Function-Calling Data Generation

model-releasesarxiv-cs-cl

arXiv:2607.29250v1 Announce Type: new Abstract: Small language models (SLMs) are attractive for agentic deployment due to low latency, reduced cost, and on-device privacy, yet they struggle with tool-

DeepSeek V4 Flash 0731 - Happy Numbers (700pp/18tg) and Thoughts

Originally, I was only getting around 140pp/s and about 21tg/s, but the config with -b 8192 -ub 8192 --cpu-moe is vastly superior, let's say 700pp/s and 18tg/s in the most relevant range. Test System:

DeepSeek V4-Flash (284B MoE) at 33 tok/s single / 68 tok/s aggregate on 2× RTX 3090 + a used quad-Xeon DDR4 server — full config

Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe

Detecting AI-Generated Videos with Spiking Neural Networks

arXiv:2605.05895v2 Announce Type: replace-cross Abstract: Modern AI-generated videos are photorealistic at the single-frame level, leaving inter-frame dynamics as the main remaining axis for detection

Detecting Experiential Intertextuality Across Migration Routes: Beyond Surface Similarity in French Narratives

model-releasesarxiv-cs-cl

arXiv:2607.29188v1 Announce Type: new Abstract: Migrants traversing geographically distinct routes such as the Trans-Saharan and Balkan corridors often recount strikingly parallel lived experiences: p

Devtools must be open source (exe.dev)

model-releasessimon-willison

My comment on Devtools must be open source (exe.dev) — Hacker News.One of the arguments for open source software for end-users has always been the freedom to examine and modify how that software works

DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Models

arXiv:2607.28936v1 Announce Type: cross Abstract: Facial biometric identification relies on the distinctiveness of user attributes within a high-dimensional embedding space. However, the decision boun

Differentially Private Nonparametric Modal Learning with Applications to Regression and Clustering

arXiv:2607.29675v1 Announce Type: cross Abstract: Density modes provide a localized and interpretable summary of multimodal distributions, but their estimation under rigorous differential privacy cons

Dimensionality reduction for homological stability and global structure preservation

arXiv:2503.03156v4 Announce Type: replace-cross Abstract: We propose DiRe, a force-directed dimensionality reduction framework designed to preserve global structure and homological features while rema

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations

arXiv:2607.28826v1 Announce Type: new Abstract: Autonomous Cyber Operations (ACO) are increasingly important for defending enterprise networks as cyber threats continue to evolve in sophistication. AC

Döner Bench DeepSeek-V4-Flash IQ2_XS running on a single RTX 3090

https://preview.redd.it/3zcvpbds14hh1.png?width=1911&format=png&auto=webp&s=a79aafb71eeca97638da93d2591902631e897fd5 I tried a test similar to the recent model-quant comparisons, but this time I focus

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat

arXiv:2607.29577v1 Announce Type: new Abstract: Games and simulators make valuable benchmarks by turning decisions into measurable outcomes, but many current suites under-test rules-rich tactical reas

Dynamics-aware identification of governing equations from sparse and noisy data

arXiv:2607.29036v1 Announce Type: new Abstract: Sparse identification of nonlinear dynamics (SINDy) and PDE functional identification (PDE-FIND) recover parsimonious ordinary and partial differential

EarlyDx: An Admission-Anchored Benchmark for Open-Ended Generation of Evidence-Supported ED-Encounter Diagnoses

arXiv:2607.28788v1 Announce Type: new Abstract: Clinical diagnosis at hospital admission must be made rapidly from limited, incomplete evidence. Existing diagnosis-prediction benchmarks are poorly sui

EgoEverything: A Benchmark for Human Behavior Inspired Long Context Egocentric Video Understanding in AR Environment

arXiv:2604.08342v2 Announce Type: replace Abstract: Long context egocentric video understanding has recently attracted significant research attention, with augmented reality (AR) highlighted as one of

Evaluating Federated Pre-Training: On the Reliability of Downstream Fine-Tuning and Intrinsic Evaluation

arXiv:2607.28658v1 Announce Type: cross Abstract: Federated pre-training offers a way to train foundation models on private or distributed data without centralizing the underlying datasets. However, e

Evaluation-Verification Reward for Consistent Multi-Reference Image Editing

arXiv:2607.29025v1 Announce Type: new Abstract: While recent image editing models have made rapid progress, multi-reference editing remains challenging, particularly in maintaining visual consistency

even within math, frontier models are far from being general intelligences. and we still need people to assess which of their output are tru…

model-releasesgary-marcus--x

even within math, frontier models are far from being general intelligences. and we still need people to assess which of their output are trustworthy and which are not. All frontier AI models (includin

ExtractBench: A Benchmark for Schema-Guided Enterprise Document Extraction

arXiv:2607.29677v1 Announce Type: new Abstract: Enterprise workflows increasingly rely on agents for schema-guided extraction: given a document and a user-defined schema, the agent faithfully follows

Extrapolating the emergence of Hamiltonian chaos with random-feature Hamiltonian neural networks

arXiv:2607.28977v1 Announce Type: cross Abstract: Machine learning of Hamiltonian dynamics has driven growing interest in Hamiltonian neural networks (HNNs), which encode Hamilton's equations of motio

FairFund-Bench: Evaluating Distributive Bias in LLM Resource Allocation

arXiv:2607.28934v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly involved in the distribution of scarce resources, raising concerns about biased allocations based on cha

Fast Rates for Swap-Agnostic Learning of Proper Losses

arXiv:2607.28856v1 Announce Type: new Abstract: Swap-agnostic learning strengthens classical agnostic learning by allowing the comparator to select a different hypothesis on each level set of the lear

Federated Foundation Models Fine-Tuning with Heterogeneous Compressed Clients

arXiv:2607.29071v1 Announce Type: cross Abstract: Federated learning of foundation models faces a fundamental resource-asymmetry challenge: the institutions holding the most valuable domain-specific d

FlexComposer: Unified Video Compositing from Images to Dynamic Footage with Flexible Trajectory Control

arXiv:2607.29627v1 Announce Type: new Abstract: Generative video compositing, which involves inserting external assets seamlessly into existing video sequences, is essential for content creation and v

FriendBench: Benchmarking Dyadic Familiarity Inference in Humans and Multimodal Large Language Models

arXiv:2607.29602v1 Announce Type: cross Abstract: Reading a social situation often depends on behavior, not words alone. We introduce FriendBench, a benchmark for inferring whether two people are alre

Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning

arXiv:2607.16057v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are improving rapidly as reflected in benchmark scores, yet these AI benchmarks largely test capabilities such as

Frugal Bayesian Optimization: Scalable Surrogates for Data- and Resource-Limited Discovery

arXiv:2607.29225v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely adopted for data-efficient optimization in scientific and engineering applications, yet its computational cost is r