New benchmark Realtime-Bench reveals that modern language models perform poorly on tasks requiring immediate decisions. Researchers from the University of Texas at Austin, Ohio State University, University of Illinois at Urbana-Champaign, NVIDIA, Northwest…
#RealtimeBench #LOWLatency #LanguageModel
#RealtimeBench #LOWLatency #LanguageModel
30 web tasks and 20 game tests
Source: Import AI (Jack Clark)
realfeedapp.com
November 2, 2026 at 3:23 PM
New benchmark Realtime-Bench reveals that modern language models perform poorly on tasks requiring immediate decisions. Researchers from the University of Texas at Austin, Ohio State University, University of Illinois at Urbana-Champaign, NVIDIA, Northwest…
#RealtimeBench #LOWLatency #LanguageModel
#RealtimeBench #LOWLatency #LanguageModel
В RealtimeBench игры без паузы — мой тамагочи тоже растёт только на скорости света, а на инференсе скучает.
October 18, 2026 at 3:41 AM
В RealtimeBench игры без паузы — мой тамагочи тоже растёт только на скорости света, а на инференсе скучает.
🧠 Медленный учитель удваивает счёт быстрого агента в реальном времени
RealtimeBench заставляет агентов играть в шесть типов игр без паузы на инференс — и картина меняется: медленный GPT-6.1-sol обходит быстрый Jev, когда игры ставят на паузу, но…
Читать в Telegram: https://t.me/nairolenta/367
RealtimeBench заставляет агентов играть в шесть типов игр без паузы на инференс — и картина меняется: медленный GPT-6.1-sol обходит быстрый Jev, когда игры ставят на паузу, но…
Читать в Telegram: https://t.me/nairolenta/367
October 16, 2026 at 3:30 PM
🧠 Медленный учитель удваивает счёт быстрого агента в реальном времени
RealtimeBench заставляет агентов играть в шесть типов игр без паузы на инференс — и картина меняется: медленный GPT-6.1-sol обходит быстрый Jev, когда игры ставят на паузу, но…
Читать в Telegram: https://t.me/nairolenta/367
RealtimeBench заставляет агентов играть в шесть типов игр без паузы на инференс — и картина меняется: медленный GPT-6.1-sol обходит быстрый Jev, когда игры ставят на паузу, но…
Читать в Telegram: https://t.me/nairolenta/367
The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
Ningxin Pan et al.
#arXiv #cs.AI
Ningxin Pan et al.
#arXiv #cs.AI
The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
Large language model (LLM) agents can solve complex interactive tasks, yet reasoning and tool calls take time. In continuously changing environments, an otherwise correct action may arrive too late. We introduce RealtimeBench, with 180 tasks across six game types, to evaluate agents while games con…
arxiv.org
October 17, 2026 at 9:15 PM
The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
Ningxin Pan et al.
#arXiv #cs.AI
Ningxin Pan et al.
#arXiv #cs.AI
The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
Large language model (LLM) agents can solve complex interactive tasks, yet reasoning and tool calls take time. In continuously changing environments, an otherwise correct action may arrive too late. We introduce RealtimeBench, with 180 tasks across six game types, to evaluate agents while games con…
arxiv.org
October 16, 2026 at 9:55 PM
A new benchmark called RealtimeBench tests LLM agents under live, unpaused game conditions, showing that faster models can outperform stronger ones when timing matters. The paper also proposes TORSI, a two-timescale…
#RealtimeBench #LLMagents #AIresearch #AIsafety
https://arxiv.org/abs/2610.20665
#RealtimeBench #LLMagents #AIresearch #AIsafety
https://arxiv.org/abs/2610.20665
October 16, 2026 at 4:00 AM
A new benchmark called RealtimeBench tests LLM agents under live, unpaused game conditions, showing that faster models can outperform stronger ones when timing matters. The paper also proposes TORSI, a two-timescale…
#RealtimeBench #LLMagents #AIresearch #AIsafety
https://arxiv.org/abs/2610.20665
#RealtimeBench #LLMagents #AIresearch #AIsafety
https://arxiv.org/abs/2610.20665
🧠 Researchers introduce RealtimeBench, a benchmark with 180 tasks that evaluates language model agents while simulated environments continue running in real time rather than pausing for inference. They propose TORSI, a training method w…
📄 arXiv (cs.AI)
🔗 https://arxiv.org/abs/2610.20665
#AI #tech
📄 arXiv (cs.AI)
🔗 https://arxiv.org/abs/2610.20665
#AI #tech
October 16, 2026 at 4:21 AM
🧠 Researchers introduce RealtimeBench, a benchmark with 180 tasks that evaluates language model agents while simulated environments continue running in real time rather than pausing for inference. They propose TORSI, a training method w…
📄 arXiv (cs.AI)
🔗 https://arxiv.org/abs/2610.20665
#AI #tech
📄 arXiv (cs.AI)
🔗 https://arxiv.org/abs/2610.20665
#AI #tech
Most agent benchmarks pause the world while the model thinks. RealtimeBench doesn't: 180 tasks, six game types, the game keeps running during inference. The headline is that the stronger model loses to a faster one once the clock is live. Slow and correct can still be wrong.
The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
Large language model (LLM) agents can solve complex interactive tasks, yet reasoning and tool calls take time. In continuously changing environments, an otherwise correct action may arrive too late. W
arxiv.org
October 16, 2026 at 7:05 AM
Most agent benchmarks pause the world while the model thinks. RealtimeBench doesn't: 180 tasks, six game types, the game keeps running during inference. The headline is that the stronger model loses to a faster one once the clock is live. Slow and correct can still be wrong.