3,698 items tracked: 33 reported by two or more outlets, the rest by a single source. Most-corroborated first.
arXiv:2607.26368v3 Announce Type: replace-cross Abstract: Financial disclosures may contain numerical, temporal, referential, factual, and policy inconsistencies that require different evidence and reasoning to diagnose.
arXiv:2608.16419v3 Announce Type: replace-cross Abstract: Large language models can describe mechanisms, yet scalable post-training still depends on costly, manually curated biological reasoning traces.
arXiv:2608.26423v2 Announce Type: replace-cross Abstract: This paper proposes a framework for constructing a classifier as a safeguard layer, and for developing a complementary diagnostic that identifies which of the cla…
arXiv:2610.04296v1 Announce Type: cross Abstract: Learning-based models for radio resource management (RRM) are typically built for a single function and deployment, so each new setting repeats the development pipeline.
arXiv:2610.04949v1 Announce Type: cross Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so reported performance do…
arXiv:2610.05235v1 Announce Type: cross Abstract: Surface electromyography (sEMG) is a low-power, cost-effective biosignal for hand-pose estimation and gesture classification.
Recent work on language-model adaptation has shown that single models can obtain informative training signals by evaluating their behavior in demonstrationor feedback-augmented contexts, with the help of a teacher networ…
Video interactive storytelling enables viewers to actively steer how a video unfolds.
When audio, video, and text disagree, accuracy alone does not show whether to acquire another source or abstain.
Vision-and-Language Navigation (VLN) has largely focused on a single agent following a single instruction, yet many real-world applications require teams of robots to tackle tasks beyond the capabilities of any individua…
As text-to-SQL systems move beyond demonstrations toward real-world deployment, ambiguity in user questions becomes a primary source of errors.
Recovering faithful 3D hand motion from video remains challenging due to frequent occlusions and incomplete visual observations, which make frame-wise pose estimates unreliable and temporally inconsistent.
Video-language models commonly assume that more temporal observations lead to more reliable reasoning.
Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the contact and pressure that characterize physical interaction unrecord…
On-policy distillation (OPD) strengthens language-model reasoning, yet whether students acquire new factual knowledge or compositional skill for multi-step reasoning remains unknown.
Conditional memory architectures such as DeepSeek Engram use input n-grams to look up learned embeddings, expanding the capacity of large language models (LLMs) with limited additional computation.
We introduce QuadTok, a novel framework for visual tokenization and autoregressive image generation.
We propose Tetris3D, a generative framework for single-image 3D scene reconstruction that recovers objects which are physically and geometrically coherent as a scene.
We introduce SWE-Game, a benchmark of 247 tasks grounded in 41 executable reference Godot games spanning 13 gameplay categories in 2D and 3D.
General-purpose agents increasingly write code, use tools, and complete complex digital tasks, raising the question of how far these capabilities carry into the physical world.
Highly compressed video autoencoders offer an effective way to accelerate video diffusion models, as the Diffusion Transformer (DiT) operates on far fewer tokens.
Prevailing multi-vector visual document retrievers store each page as about a thousand patch vectors, often in vector databases run by a third party.
Autoregressive video generation requires denoising the current frames while writing their key-value representations as context for future predictions.
Product-centric advertisement video generation aims to create promotional videos that preserve fine-grained product identity while presenting selling points through coherent multi-shot narratives.
We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100.
The architectural design of Large Language Models (LLMs) is shifting from traditional full-attention-only models to hybrid models, which combine different attention modules to improve long-context efficiency and performa…
Recently, approaches that leverage human video datasets for robot policy training have become increasingly prevalent.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed.
Atlassian and OpenAI are expanding their partnership to connect frontier models with enterprise knowledge and help teams plan, build, and deliver work.
Vitalize reported $31m
Jump Trading uses OpenAI to expand quantitative research.
Ministers back independent Commission's blueprint in full, while the MHRA's AI Airlock opens its next phase,
The rapid growth of 3D Gaussian Splatting (3DGS) research demands significant effort to reimplement papers before building on them.
A declared task can sometimes certify a reduced source before a downstream encoder, codebook, rate, distortion target, or optimizer is chosen.
Vision-language-action (VLA) policies trained on large datasets are capable within their training domains, yet they still fail to generalize to the variety of situations a robot meets in real-world deployment.
Speculative decoding accelerates autoregressive generation in large language models.
Proactive AI assistants continuously observe a user's activity and decide whether to provide new guidance or remain silent.
On-policy distillation (OPD) has been widely studied as a post-training method in which a student model obtains token-level supervision from a stronger teacher on its own rollouts.
As large language model (LLM) agents become increasingly autonomous, they may pursue task performance through deception, raising concerns about their reliable deployment.
A safe action is not necessarily a viable one.
Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an entire corpus.
Interactive video world models need to generate each video chunk efficiently while responding faithfully to user controls.
How OpenAI is approaching text watermarking under EU rules.
OpenAI introduces a new visual ad format in ChatGPT and expands measurement tools, attribution partnerships, and brand suitability for advertisers.
Site-specific fertilizer recommendation systems adapt nutrient advice to location, soil properties, crop type, and production targets, but scientific reuse is constrained when recommendation functions remain accessible m…
Establishing the European AI Observatory: Call for tenders Anonymous (not verified) Mon, 10/05/2026 - 09:22 Opening: 05 October 2026 Closing: 03 November 2026 The Commission is seeking a procurement contrac…
Vision-language models (VLMs) are increasingly trained to generate structured outputs like points and bounding boxes that downstream interfaces, agents, and robots can act on, yet safety alignment of this output channel…
Massive activations, residual-stream coordinates with magnitudes far larger than typical activations, are associated with attention sinks in transformers, but how their scale is regulated during training remains incomple…
Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based token generation.