Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
Electrocardiography (ECG) contains subject-specific morphology that supports biometric recognition, yet image-based performance depends on how the waveform is rendered. We introduce representative-mor...
Backtest auditing is a calibration problem: high flaw recall is not useful when the model falsely flags matched clean strategies. We build a 96-item paired benchmark in which every flawed backtest has...
Video understanding is usually benchmarked on curated, single-actor, or professionally filmed clips, and a strong score there is routinely read as evidence a model is robust enough for deployment. Ama...
The key-value (KV) cache of autoregressive transformers can be viewed as a fourth-order tensor spanning attention heads, tokens, features, and grouped layers. We measure the singular-value spectra of...
Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents. This paper evaluates five open-weight 7B-8B mo...
Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage but reduces the diversity of representations ava...
The article explains how GRPO trains small language models using verifiable rewards, focusing on the mechanics of local reasoning experiments with Unsloth. It emphasizes that the reward function is as crucial as the model itself in shaping the training process. The post was originally published on Towards Data Science.
Methods operating on Vision Transformer (ViT) feature spaces typically rely on Euclidean distance or cosine similarity. This assumes that every direction is equally meaningful, but there is no reason...
Pruning large pre-trained transformer-based ASR models such as OpenAI's Whisper has seen great adoption, as pruning the decoder led to significant end-to-end transcription speedups. For instance, the...
Video is a rich representation of a physical event, capturing appearance, geometry, motion, and temporal evolution. Other modalities, such as 3D body motion or audio, encode narrower aspects of the sa...
Ringg’s AI agents, powered by GPT‑5.6, can resolve up to 65% of customer calls. They operate across voice, chat, WhatsApp, and web in multiple languages. The solution delivers these capabilities at a cost 90% lower than GPT‑4.1.
The OpenAI blog article titled "Harvey turns legal context into stronger drafts with GPT-6 Astra" discusses how GPT-6 Astra generates more structured, context-aware legal documents. This capability allows lawyers to concentrate on strategic aspects of their work rather than drafting details.
Invideo is leveraging GPT‑6 Astra to enhance its editing workflow, achieving more precise plans for edits and improving color correction and grading three times faster. The integration also enables the creation of 50 custom effects in a single day.
Reinforcement learning (RL) is widely used to sharpen reasoning in multimodal large language models (MLLMs), yet its effect on hallucination is uneven. We trace this to two weak points in the \emph{co...
In-Context Learning (ICL) has become a cornerstone of modern LLM deployment. However, existing ICL post-training methods have a critical blind spot: they excel at extracting patterns from demonstratio...
Modern large language models are pretrained on massive datasets, making it difficult to prevent benchmark data from entering their training sets and undermining the reliability of evaluation results....
Vision-language models (VLMs) are often reported to outperform task-specific vision backbones for unmanned aerial vehicle (UAV) power-line defect assessment. We test that claim on ElecVQA-Bench, a 56,...
Compact vision-language models (VLMs) now power a growing share of multimodal applications. The benchmarks used to compare them, however, inherit a frontier-centric design: each model is reduced to a...
Video provides a rich record of human behavior, interaction, and situated contexts, offering important evidence for understanding people and conducting human-centered research. As vision-language mode...
arXiv:2609.26347v1 Announce Type: cross Abstract: The scarcity of non-English language data in specialized domains significantly limits the development of effective Natural Language Processing (NLP)...