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VECTOR WIREAI INTELLIGENCE
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AI Research Radar

September 23–29: 23 frontier papers out of 3,173 read.

23 frontier270 cleared3,173 papers read

Frontier

Papers rated as moving the field

How we choose

RMB

“Our extensive experiments demonstrate that RMB significantly improves reward accuracy on both in-distribution and out-of-distribution datasets, substantially mitigating the reward hacking issue and ultimately improving RLHF performance.”

SafetyTencent

Pistis Technical Report

“Experiments demonstrate that PAH enhances the model performance without updating the model parameters or increasing the interaction budget.”

TrainingByteDance

Hunyuan-A13B Technical Report

“Evaluations show competitive performance across mathematics, science, programming, general language understanding, and agent tasks, often approaching that of much larger models.”

TrainingTencent

AgentWorld

“Experiments with Gemini 3 Flash, Claude Haiku 4.5, GPT-5 Mini, and DeepSeek R1-70B show that even the best model achieves only 52.0% task success, with systematic failure modes including communication breakdowns, role confusion, and inability to maintain shared plans across rounds.”

AgentsBenchmark

RE-0

“Experiments across multiple Code-as-Policy embodied tasks show that RE-0 improves both teacher-assisted execution and the standalone student, and generalizes to novel robots and scenes.”

Agents

PROACT-Agent

“In AgentDojo, it reduces non-DoS targeted attack success from 20.82% to 0.40%.”

Safety

Your Model Is Leaking

“Across eleven models from seven architecture families, our evaluation shows 91--100% recovery on nine models with KL divergence 0.001--0.007, while evaluated activation-level detectors remain close to random guessing (AUC <= 0.56).”

Security

Qwen3.8-Omni

“Extensive evaluations demonstrate that Qwen3.8-Omni-Flash achieves strong performance across multimodal understanding, reasoning, long-horizon agentic execution, and video productivity tasks.”

Agents

Despite Instructions

“We find that model pairs can learn to communicate the secret using only one bit of feedback indicating whether the receiver inferred it correctly.”

Safety

Distillation Defenses Easily Break After Reinforcement Learning

“We show that simple attacks can steal reasoning capabilities from existing closed-source language models using data easily obtainable from current APIs, yielding reasoning improvements equivalent to more sophisticated attacks that extract the full hidden traces.”

Security

Delegated Misalignment

“We show that this assumption breaks down: \emph{individual safety alignment fails to transfer to multi-agent settings}.”

Safety

The week by field

Sep 23–29: 270 cleared, 23 frontier

Also cleared

247 papers, by field

Security & privacy95
All 95 papers in Security & privacy
Safety & alignment49
All 49 papers in Safety & alignment
Agents30
All 30 papers in Agents
Language & speech18
All 18 papers in Language & speech
Vision & multimodal13
All 13 papers in Vision & multimodal
AI & society11
All 11 papers in AI & society
Inference & efficiency10
All 10 papers in Inference & efficiency
Robotics & embodied AI8
All 8 papers in Robotics & embodied AI
Science & health6
Machine learning3
Reasoning & math2
Training & data2