Search: “openai”

arXiv:2501.01669v4 Announce Type: replace Abstract: Inverse reinforcement learning (IRL) has progressed significantly toward accurately learning the underlying rewards in both discrete and continuous

arXiv:2605.27440v1 Announce Type: cross Abstract: Small changes to how a buyer phrases a question -- 'best CRM' vs 'top CRM' vs 'best CRM for a SaaS startup' -- produce substantially different brand r

arXiv:2605.28065v1 Announce Type: new Abstract: AI agents are increasingly useful for biological data analysis, but existing benchmarks mostly test broad biological knowledge, executable workflows, or

Artificial intelligence training data provider Human Archive Inc. today announced that it has raised 8.2 million in funding. Wing Venture Capital, NVP Capital, Y Combinator headlined the consortium th

arXiv:2605.27072v1 Announce Type: cross Abstract: We present E3, an automated review assistant that augments reviewers and engineering teams by identifying decision-relevant technical concerns in rese

I really appreciate the lessons and technical ideas @samaysham & team were able to share about their tax agent system, which learns from production traces to self-improve via detailed tracing tightly

“Tokens got burned for millions of dollars without any real significant ROI to show for it.” hearing this over and over again The same conversation is happening across tech right now and many of us sa

U.S. law enforcement agencies are monitoring growing backlash to AI and have begun classifying anti-technology sentiment as an extremism threat, with unpublished reports from the Department of Homelan

arXiv:2605.25454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being used for emotional support. They are also being developed for formal therapy purposes. However, LL

arXiv:2605.24053v1 Announce Type: new Abstract: Large Language Models (LLMs) are predominantly governed by probabilistic frameworks in which the sum of outcome probabilities is constrained to unity. T

arXiv:2605.25893v1 Announce Type: new Abstract: Despite the emergence of diffusion large language models (D-LLMs) as an alternative to autoregressive large language models (AR-LLMs), safety monitoring

arXiv:2509.13608v2 Announce Type: replace Abstract: As Large Multimodal Models (LMMs) become integral to daily digital life, understanding their safety architectures is a critical problem for AI Align

arXiv:2505.23764v3 Announce Type: replace-cross Abstract: Spatial intelligence is essential for multimodal large language models (MLLMs) operating in the complex physical world. Existing benchmarks, h

Nano Banana Pro vs. GPT Image 2 Nano Banana Pro wins on photorealism, 4K output, 14 reference image slots for product/scene consistency, and live web search for real-world accuracy. GPT Image 2 wins o

arXiv:2507.10593v3 Announce Type: replace-cross Abstract: Every LLM tool call is structurally an RPC -- a function name, JSON arguments, and a serialized result -- yet each protocol (native Python, MC

New York Times: A look at the UK's AI Safety Institute, whose researchers probe AI models for safety gaps, as its work becomes a blueprint for other governments' AI policies — The government's A.I. Se

An open source model has returned to #1 on the 3D Design leaderboard by Design Arena. Kimi K2.6 has reached the top of the leaderboard for 3D Design, ahead of models 10X more expensive like Opus 4.7 b

arXiv:2605.23497v1 Announce Type: new Abstract: Large language models are increasingly used for legal research, yet their fixed training cutoffs and reliance on static parametric knowledge are at odds

arXiv:2605.23415v1 Announce Type: cross Abstract: Reinforcement learning has long struggled with poor sample efficiency. One promising approach to mitigate this problem is leveraging group-invariant M

arXiv:2411.01332v5 Announce Type: replace Abstract: Despite significant advancements in XAI, scholars note a persistent lack of solid conceptual foundations and integration with broader scientific dis

I once asked a bunch of e/accs how much damage was an acceptable risk relative to take (any) safety precautions. none answered. we may be about to find out. One implication of the below is that we rea

it ain’t just me who sees the emperor has no clothes The AI bubble math doesn't add up. Anthropic spends 3 to make 1 and that’s before you include any and all other costs like staff or electricity. Mi

arXiv:2605.21653v1 Announce Type: cross Abstract: AI text detectors amplify a pretrained typicality axis; they do not construct an AI-vs-human boundary. On raw encoders before any task supervision, pr

arXiv:2506.11060v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code rema

I truly miss the age of science and transparency in AI. Especially given how much money and political power and governance and scientific understanding is at stake. We don’t know for example • How man

arXiv:2605.21470v1 Announce Type: new Abstract: Computer-use agents (CUA) automate tasks specified with natural language such as 'order the cheapest item from Taco Bell' by generating sequences of cal

can’t believe people assume that success on highly verifiable problems in math (where we don’t even know how many tests were performed and how many might have failed) iautomatically generalize to ever

proof too complicated, Claude help ELI5 Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematician

🚀Qwen3.7-Max just landed at 56.6 on the Artificial Analysis Intelligence Index — a solid 4.8pt jump over Qwen3.6-Max-Preview. @ArtificialAnlys ⚡️Sharper sci reasoning, stronger agentic chops, better c

It’s a really special time to be alive…some thoughts from training this model 🧵 Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in

Once AI starts making solving open problems in novel ways it won’t stop. We are entering the final stage of human solutions to open problems like this. Feels weird, doesn’t it? Today, we share a break

arXiv:2605.19932v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over long and recurring external contexts, like document corpora and code repositories. Across in

the crazy part is that people are “clowning” me without knowing anything about the training or whether anything else other than scaled changed or how the model does on anything else. (or what it costs

three of the things we are most excited about: 1. AGI accelerating research 2. AGI accelerating companies 3. personal AGI accelerating everyone in achieving their goals today it was great to announce

arXiv:2204.01611v3 Announce Type: replace Abstract: Inspired by the cognitive science theory, we explicitly model an agent with both semantic and episodic memory systems, and show that it is better th

arXiv:2509.21820v2 Announce Type: replace Abstract: In this paper, we introduce a combination of novel and exciting tasks: the solution and generation of linguistic puzzles. We focus on puzzles used i

arXiv:2605.18327v1 Announce Type: new Abstract: AI agents deployed into SRE workflows currently derive their understanding of environment state from raw observability telemetry at query time, paying a

Artificial intelligence developer Decart.ai Inc. today announced that it has raised 300 million in funding at a nearly 4 billion valuation. Radical Ventures led the round with participation from Nvidi

arXiv:2605.17625v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into persistent scientific collaborators, context window saturation has emerged as a critical bottleneck. Scienti

arXiv:2605.17554v1 Announce Type: new Abstract: Frontier deep research agents (DRAs) plan a research task, synthesize across documents, and return a structured deliverable on demand. They are being de

arXiv:2511.21654v2 Announce Type: replace Abstract: We introduce EvilGenie, a benchmark for reward hacking in programming settings. We source problems from LiveCodeBench and create an environment in w

arXiv:2605.17246v1 Announce Type: cross Abstract: We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a c

I put together these annotated slides from my five minute lightning talk at PyCon US 2026, using the latest iteration of my annotated presentation tool. # I presented this lightning talk at PyCon US 2

arXiv:2605.17928v1 Announce Type: cross Abstract: Transfer Learning, a technique where a model/agent can use the knowledge/expertise that it gained from one task and exploit that to solve another clos

arXiv:2605.17691v1 Announce Type: cross Abstract: Automating the classification of negative treatment in legal precedent is a critical yet nuanced NLP task where misclassification carries significant

arXiv:2510.16252v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for web agents demands environments that are both effective for evaluation and efficient enough for large-scale on