Knowledge catalogue
arXiv:2607.29601v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) commonly adapts large language models using a single shared Low-Rank Adapter (LoRA). This shared optimization spa
arXiv:2607.29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as fo
OpenAI has redesigned the ChatGPT Voice stack—from client to model—to enable continuous audio streaming, allowing GPT‑Live to listen while speaking without interruption. The new architecture supports
The results span sphere packing, coding theory, group theory, quantum complexity, lattice cryptography, extremal combinatorics, and more. Among them: establishing the existence of non-sofic groups and
arXiv:2607.29624v1 Announce Type: cross Abstract: Traditional static assessments rely on a subtractive, deficit-based grading model that often penalizes ambition and obscures diagnostic feedback. Conv
There should be a public investigation into the AI hacking incidents by OpenAI and Anthropic. We deserve to know whether these labs are genuinely world-class security organizations facing a novel thre
arXiv:2607.28642v1 Announce Type: new Abstract: Long chain-of-thought reasoning improves performance on complex problems, but it also introduces redundancy accumulation, context overflow, and error an
This is a wild result. Locus, the automated research system from @intology, post-trained Qwen3 base models that beat the official human-tuned Qwen3 1.7B Instruct release. SoTA on PostTrainBench! The m
this is the real reason people from OpenAI etc are desperate to shut me up. Astra (which didn’t even have a control group and is maybe not that much better than Fable and certainly not ASI) was perhap
arXiv:2308.08794v4 Announce Type: replace Abstract: Tipping points are abrupt, drastic, and often irreversible changes in the evolution of non-stationary and chaotic dynamical systems. For instance, i
arXiv:2607.28887v1 Announce Type: cross Abstract: Large language models increasingly write and repair production code, yet evidence is mounting that their test-passing patches leave codebases harder t
arXiv:2607.28643v1 Announce Type: cross Abstract: Automating facilitation in online discussions is a long-standing social concern given the increasing time we spend on online spaces and the failure of
arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r
arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie
arXiv:2607.09598v2 Announce Type: replace Abstract: Lightweight speech recognition models are critical for edge deployment, yet highly optimized architectures like Moonshine often fail on morphologica
arXiv:2607.28640v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) should generate consistent responses given semantically equivalent inputs across modalities. However, we observ
arXiv:2607.29678v1 Announce Type: new Abstract: LLM serving systems cache prompt KV state, yet most front ends still re-tokenize the full request text on every call. The cost lands on coding agents, w
arXiv:2607.29592v1 Announce Type: new Abstract: The primary challenge of continual learning (CL) systems is to learn new tasks while remaining performant on previously learned tasks. A similarly impor
arXiv:2607.29254v1 Announce Type: new Abstract: AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential
arXiv:2607.28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate
arXiv:2607.28896v1 Announce Type: cross Abstract: Unified audio models capable of audio understanding, audio generation and, increasingly, audio editing are proliferating rapidly. Yet a basic question
arXiv:2607.29684v1 Announce Type: new Abstract: Robust low-light imaging remains challenging for the community. Recent studies have explored fusing Near-Infrared (NIR) with noisy RGB to achieve improv
arXiv:2603.11257v2 Announce Type: replace Abstract: Cardiac and lung ultrasound are technically demanding because operators must identify patient-specific intercostal acoustic windows and then navigat
arXiv:2509.06342v2 Announce Type: replace Abstract: Legged robots must achieve both robust locomotion and energy efficiency to be practical in real-world environments. Yet controllers trained in simul
arXiv:2601.22546v2 Announce Type: replace-cross Abstract: The recent advancements in Large Language Models (LLMs) have attracted interest in exploring their in-context learning abilities and chain-of-
arXiv:2507.21799v2 Announce Type: replace-cross Abstract: The empirical success of deep learning has spurred its application to the radio-frequency (RF) domain, leading to significant advances in Deep
arXiv:2604.01207v2 Announce Type: replace Abstract: Existing 3D Gaussian Splatting (3DGS) editing methods primarily focus on appearance modification and often struggle to support flexible geometry edi
arXiv:2607.29586v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) tests whether a model can infer an unseen transformation from a few input-output examples and apply it to a
arXiv:2607.29285v1 Announce Type: new Abstract: Action chunking shortens the effective decision horizon of robot imitation learning by predicting multiple future actions, while conventional phase cond
arXiv:2607.29278v1 Announce Type: new Abstract: Existing cross-domain few-shot segmentation approaches suffer from high training costs due to source-domain episodic training and pixel-wise dense predi
arXiv:2607.29496v1 Announce Type: new Abstract: We study transcript management for fixed, finite-precision causal Transformers. A transcript is partitioned into channels of bounded blocks. Each transi
arXiv:2607.29567v1 Announce Type: new Abstract: Manipulating transparent laboratory glassware that contains liquid is inherently safety-critical: even small geometric errors can cause unstable grasps
arXiv:2607.29287v1 Announce Type: cross Abstract: Multi-domain machine translation (MDMT) poses a unique challenge due to varying levels of linguistic complexity across domains. Inspired by human tran
arXiv:2607.29032v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting
arXiv:2607.29145v1 Announce Type: cross Abstract: Quantum software engineering is an emerging research field focusing on efficiently embedding the quantum programming paradigm into existing software e
arXiv:2607.29500v1 Announce Type: new Abstract: Cable-Driven Parallel Robots (CDPRs) are a type of parallel mechanism in which cables are used as actuators. Due to the two levels of redundancy and num
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Humanoid robots usually elicit more cringe than awe: They stum
Try Qwen3.8-Max on Hermes Agent and you will have to doubt on how much these open frontier models have caught up with frontier closed models. These new open models are insanely good. Meet Qwen3.8-Max:
two weeks ago i went on @swyx's pod and said some things that i... should not have said. a lot has happened since then, i owe you all an apology. i'm sorry that i was right about every single thing. a
arXiv:2607.29200v1 Announce Type: new Abstract: Ultrasound imaging has become increasingly widespread in clinical practice due to its portability, low cost and real-time capability, making ultrasound
arXiv:2607.28650v1 Announce Type: cross Abstract: While industry discourse often emphasizes immediate productivity gains and frames GenAI primarily as a tool for automation, the integration of GenAI i
arXiv:2607.28769v1 Announce Type: new Abstract: Security-critical biometric and forensic applications require accurate predictions and reliable confidence estimates, particularly under distribution sh
Preference alignment has become a crucial component in enhancing the performance of Large Language Models (LLMs), yet its impact in Multimodal Large Language Models (MLLMs) remains comparatively under
arXiv:2407.04521v3 Announce Type: replace-cross Abstract: This paper studies the continuous-time q-learning in mean-field jump-diffusion models in a setting where the environment simulator does not pr
To make informed decisions, businesses often need to connect their internal data with public reference data, to create a knowledge graph that connects real-world things and their relationships. Howeve
arXiv:2607.29256v1 Announce Type: new Abstract: Designing polyimide structures with specific glass transition temperatures (Tg) is highly challenging. Existing methods primarily focus on target-condit
Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI). When the variables to be inferred are continuous, it makes sen
Spent way too much time with V4-Flash-0731 this weekend and wanted to share my vibes as briefly as possible. I sent it through a bit of real-work and some of my personal benchmarks. My quick thoughts
arXiv:2607.28871v1 Announce Type: cross Abstract: When a repair agent runs a test and sees it pass, the result is treated as evidence about the reported defect. We measure how often that treatment is
arXiv:2607.29353v1 Announce Type: cross Abstract: With the ever-increasing pervasiveness of smart edge devices, the demand is growing for applications that can be tailored to users (e.g., custom keywo
arXiv:2607.29370v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) aims to detect and localize anomalies in unseen categories without access to target-specific training data. Although
Katherine Hamilton / Wall Street Journal: Visa plans to acquire Israeli company BioCatch, which uses AI to detect fraud and distinguish legitimate users from attackers in real time, for $2.4B in cash
arXiv:2607.28678v1 Announce Type: new Abstract: Multimodal agents operating in long-horizon environments must build and continually update multimedia memories to support entity-consistent, temporally
arXiv:2601.00610v2 Announce Type: replace Abstract: Reinforcement learning (RL) has strong potential in robotics, but exploration-based training complicates safe deployment on large-scale robots. For
arXiv:2607.28967v1 Announce Type: new Abstract: Prompt tuning adapts vision--language models with few trainable parameters, but existing approaches trade off efficiency and adaptation: static textual
arXiv:2607.29102v1 Announce Type: new Abstract: Realistic palpation training requires reliable rendering of soft tissue stiffness changes in real time, which is difficult to achieve with conventional
arXiv:2607.28760v1 Announce Type: cross Abstract: As image generation models scale to ever higher resolutions, global coherence, local detail, and texture fidelity become critical axes for generation
arXiv:2508.03343v2 Announce Type: replace Abstract: Text-Motion Retrieval (TMR) aims to retrieve 3D motion sequences semantically relevant to text descriptions. However, matching 3D motions with text
Id figured since they first emailed people about api price changes coming mid july then delayed the v4 flash release to late july, I wonder if they delayed it for the sake of stealing spotlight from o
arXiv:2607.29613v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training of Vision-Language-Action (VLA) models has shown strong promise for robotic manipulation. Among RL methods,