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VECTOR WIREAI INTELLIGENCE
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AI Research Radar

August 13–19: 11 frontier papers out of 1,882 read.

11 frontier179 cleared1,882 papers read

Frontier

Papers rated as moving the field

How we choose

StartupBench

“Our results reveal that many market-validated workflows remain beyond the reliable capabilities of current general-purpose agents, establishing StartupBench as an empirical measure of progress toward E2E completions of real-world user tasks.”

The authors, in the abstract

Benchmarking General-Purpose Agents on Market-Validated End-to-End Workflows

ByteDanceBenchmarkarXivPDF

Debate Training Reduces Reward Hacking in RLAIF

“We show that critique word limits (effective up to 150 words) successfully balance the game and avoid judge hacking, though this introduces a trade-off by restricting critic expressive clarity.”

Google

EgoMonth

“Evaluation of state-of-the-art open-source and closed-source MLLMs reveals that even the best-performing model, Gemini 2.5 Pro, achieves only 71.8% macro-average accuracy, remaining 22.4 percentage points below the corrected human baseline of 94.2%.”

Benchmark

FrontierFinance

“Evaluating frontier models and agent systems under a common harness restricted to publicly available data, we find that the tool harness, not the model alone, strongly shapes quality and efficiency; that Samaya's in-house system leads at 56.0%, ahead of the strongest frontier model (Claude Fable 5, 49.2%) at roughly 2.2x lower cost; and that the best open-weight model (Kimi K3, 46.4%) nearly matches the best proprietary model at 4.5x lower cost.”

Benchmark

Practice Makes Unsafe

“Across representative skill evolution methods, SafeEvolve reduces unsafe retrieval and fresh-session harm by 26.7 and 17.3 percentage points, respectively, while mean benign utility changes by only 0.4 points.”

Rubric Dropout

“Sweeping the dropout fraction shows a broad 30-50% sweet spot, while the natural alternative, reweighting criteria by how useful they are to training, performs worse than no intervention at all in our setting.”

Omni-LiveAvatar

“Extensive experiments show that Omni-LiveAvatar generates high-quality, synchronized minute-level avatars in real time.”

The week by field

Aug 13–19: 179 cleared, 11 frontier

The week’s papers have not been sorted into fields yet.

Models under test

Papers this week that name the model

  1. GPT-5.6 Sol5
  2. GPT-5.53
  3. GPT-4o mini3
  4. GPT-4o3
  5. Claude Sonnet 4.62
  6. GPT-5.42
  7. DeepSeek-V4-Pro2
  8. Kimi K32

Labs publishing

Papers this week with an author at the lab

  1. Tencent5
  2. Google3
  3. Alibaba2
  4. IBM2
  5. Meta2
  6. Microsoft2
  7. NVIDIA2
  8. ByteDance1

Also cleared

168 papers

All 168 papers