Search: “gpt”

Users on the r/ChatGPT subreddit have reported intermittent system errors when attempting to generate images via ChatGPT, a recurring issue that has affected various user tiers over time. OpenAI ha...

arXiv:2603.09677v3 Announce Type: replace Abstract: Addressing the challenges of fragmented task definitions and the heterogeneity of unstructured data in multimodal parsing, this paper proposes the O

arXiv:2603.10512v2 Announce Type: replace Abstract: Artificial intelligence has advanced significantly through the development of intelligent game-playing systems, providing rigorous testbeds for deci

arXiv:2604.06427v1 Announce Type: cross Abstract: The viability of chain-of-thought (CoT) monitoring hinges on models being unable to reason effectively in their latent representations. Yet little is

A Reddit thread on r/ChatGPT discusses user frustration with ChatGPT resisting internet search requests and seemingly contradicting user-provided information. This behavior stems from two core issu...

@3blue1brown https://x.com/verncrawford/status/2042344703077859402?s=46 @NousResearch 2 prompts guys. 2 prompts!!! The second prompt was “go from 6 camera moves to 3.” (Hermes Agent, Codex5.4, Manim V

After playing with it a bit, Meta's Muse Spark Thinking is fine so far, but really doesn't match the current Big Three models. It also is a bit... weird. Like some strange language & tone, a little lo

Early Beta Support for Blue Bubbles iMsg as a Gateway is now in Hermes Agent. Now you can use iMessage as an interaction layer for your agent. Test early by using hermes update and setting it up! Let

Across the hospitality industry, the AI-driven guest experience is emerging as the new standard for efficiency and personalization, reshaping what guests expect and what staff are asked to do. Wynn Re

Routing every task to your largest model burns tokens, adds latency, and inflates costs. @AI21Labs' Maestro Orchestration Meta Model (OMM) is the layer above your stack that dynamically selects the ri

Hermes Agent is an open-source, self-improving AI agent developed by Nous Research that features a built-in learning loop — it creates skills from experience, builds persistent memory across sessio...

The Nous Research Portal (portal.nousresearch.com) is the account and API management hub for Nous Research's inference offerings. Nous Research launched an Inference API serving its open-source mo...

A crypto/DeFi developer named banteg posted on X (Twitter) observing that Dario Amodei was still at OpenAI in 2019, where he worked under Sam Altman from 2016 to 2020 as VP of Research, playing an...

Hermes Agent's **Profiles** feature, introduced by Nous Research, enables multi-instance operation — allowing users to run multiple isolated Hermes instances from a single installation, where each ...

I spent the night testing open-source coding models against Claude Opus in production. Same codebase. Same tasks. Real API calls, real file edits, real bugs. Tested: Arcee Trinity-Large-Thinking, http

NousResearch's Hermes Agent is an open-source personal agent that serves as a successor/migration target for the lobster-themed OpenClaw agent. Users experiencing issues after a recent update can m...

AlphaXiv introduced GLM-5.1 as the underlying model powering its research paper understanding features on the alphaXiv platform, enabling users to highlight any section of a paper to ask contextual...

The chart says GLM-5.1 scored 54.9 on coding benchmarks. Three points behind Claude Opus 4.6. Interesting but not the story. The story is what trained it. Zero Nvidia GPUs. 100,000 Huawei Ascend 910B

Great application of small language models from Salesforce and colleagues. AI-scientist pipelines are well known to struggle to propose novel and diverse research ideas. This team trains an 8B reasoni

we’re getting used to it by now but DeepSeek calling this a “minor update” while moving Terminal-Bench 4.0 from 31.2 to 42.3 is very funny. also reports 77.0 on DeepSWE (vs 74.0 for Opus 5 and 73.0 fo

arXiv:2610.22298v1 Announce Type: cross Abstract: Large language models (LLMs) can generate differential diagnoses for complex cases, but a useful second opinion must also be factually grounded, clini

arXiv:2511.16221v2 Announce Type: replace-cross Abstract: Despite their advanced reasoning capabilities, state-of-the-art Multimodal Large Language Models (MLLMs) still lack a core component of human

arXiv:2610.21597v1 Announce Type: cross Abstract: Reverse engineering the data formats used by mobile software is skilled and slow, and using AI to assist with it is attractive. We evaluate this for t

arXiv:2610.21204v1 Announce Type: new Abstract: When a speaker says ``some students passed'', listeners infer that not all of them did. Reasoning models now let users decide how long a model thinks be

arXiv:2610.22360v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) and 3D generation have expanded 3D understanding and synthesis. However, beyond visual fidel

Guanzhi's deep dive thread: https://x.com/guanzhi_wang/status/2111127089428701366?s=46 ASPIRE is now open-source! Since our initial release, we've made exciting progress: 🤖 Real-world robot manipulati

arXiv:2610.20980v1 Announce Type: cross Abstract: Compiler transformations interact, making GPU kernel optimization a search for combinations that preserve the computation while improving performance.

arXiv:2610.22289v1 Announce Type: new Abstract: Stronger language models may increasingly construct useful procedures for themselves, reducing the advantage of developer-supplied scaffolding. We inves

arXiv:2610.20776v1 Announce Type: cross Abstract: LLM-based agents increasingly execute long-horizon, end-to-end workflows involving shell commands, code modification, dependency installation, and int

arXiv:2610.21502v1 Announce Type: new Abstract: Internal solitary wave (ISW) remote sensing requires task parameters and spatial information to be transferred across image acquisition, detection, stri

arXiv:2610.20634v1 Announce Type: new Abstract: Retrieval-augmented generation asks one question at volume: does this evidence support this claim? The answer is one bit, yet most pipelines obtain it f

arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w

arXiv:2610.21046v1 Announce Type: cross Abstract: Peer review is under strain from the growth of submissions, and review comments written by humans or AI can misstate what a paper says. We introduce R

Seriously, there is no way to algorithmically filter out the obvious AI slopreplies? The paper on how a team of Gemini 4 agents beat Minecraft is worth a look. It is accessible example (partially beca

arXiv:2610.20665v1 Announce Type: new Abstract: Large language model (LLM) agents can solve complex interactive tasks, yet reasoning and tool calls take time. In continuously changing environments, an

arXiv:2610.22324v1 Announce Type: new Abstract: One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of

arXiv:2610.22018v1 Announce Type: new Abstract: Arabic calligraphy is a high-stakes cultural visual domain for Muslim communities, yet VLM evaluations rarely test its fine-grained script traditions. W

arXiv:2610.22068v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can act unsafely when individually benign images and texts are interpreted jointly. Beyond implicit reasoning r

arXiv:2610.20805v1 Announce Type: new Abstract: A reasoning trace retained at answer time plays two roles: it can raise accuracy, and it can compete with the current evidence when the two disagree. We

arXiv:2610.20731v1 Announce Type: cross Abstract: Humans interpret multimodal observations of the world and forecast how it will evolve. Recent multimodal generative systems have demonstrated similar

arXiv:2610.19475v1 Announce Type: cross Abstract: Multimodal in-context learning (ICL) is an important capability of multimodal large language models (MLLMs). Its performance is closely tied to the de

arXiv:2610.18860v1 Announce Type: new Abstract: Generating information-rich visual artifacts such as slides, posters, and dashboards as code is appealing because the outputs are structured, editable,

arXiv:2610.18498v1 Announce Type: cross Abstract: Autoformalization (AF) requires more than compilation: formal statements must preserve the meaning of their informal sources, a property known as fait

arXiv:2610.20263v1 Announce Type: new Abstract: Every multilingual speech pipeline begins with a language decision, an error there propagates silently through recognition, translation and routing. In

Argon has a similar performance profile on ARC-AGI-3 as Astra. Google is back at the frontier. Gemini 4 Argon from @Google on ARC-AGI (Verified): - ARC-AGI-3: 97.5%, 4.8K (provider adapter harness), 4

arXiv:2610.19704v1 Announce Type: new Abstract: Large language models (LLMs) increasingly help users arrange appointments, plan journeys, and allocate limited resources. These tasks require models to