Pai 的 AI 雷达

模型与评测

今天:Third-party cyber ev,PCSD(Agent 原型)。并行还有 PAST-Bench、Beyond VLAs、ExplainBench。

日期
2026/08/05
今日条目
28
当前类目
26
领域金融1
#06

MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations

Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success criteria. Real-world deployments often require Long-Term Coherence, the c

推荐理由MerchantBench: Benchmarking LLM Agents:Large language model agents are increasingly evaluated as autonomous tool users, yet。
模型与评测HF daily papers
#08

Hunyuan3D-Buffalo 1.0: A Unified Multimodal Model for Scalable 3D Generation, Understanding, and Editing

Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing. However, unified 3D modeling remains constrained by scarce multimoda

推荐理由Hunyuan3D-Buffalo 1.0: A Unified:Recent advances in image generation have demonstrated the potential of unified。
模型与评测HF daily papers
#09

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling

Language remains an outlier in generative modeling: while images, video, and audio are increasingly modeled in continuous latent spaces, text generation still relies predominantly on discrete tokens. Existing continuous

推荐理由AURORA-LM: Autoencoding Unified:Language remains an outlier in generative modeling: while images, video, and audio are。
模型与评测HF daily papers
#14

Any-OPD: Heterogeneous On-Policy Distillation for Flow-Matching Models via Representation-Space Bridging

On-policy distillation, in which a teacher corrects samples that the student itself generates, presupposes that the two models speak the same language: identical VAE latents, matching architectures, and a common timestep

推荐理由Any-OPD: Heterogeneous On-Policy:On-policy distillation, in which a teacher corrects samples that the student itself。
模型与评测HF daily papers
#19

Are the Financial Reasoning from LLMs Credible? A Real World Test over Long-Horizon Statements

Do Large Language Models (LLMs) possess genuine structural reasoning, or merely rely on surface-level pattern matching? The financial domain, demanding numerical precision and multi-step logic over long contexts, is an i

推荐理由Are the Financial Reasoning from LLMs:Do Large Language Models (LLMs) possess genuine structural reasoning, or merely rely。
模型与评测HF daily papers
#23

RestoreKV: Recovering Full-Cache Behavior Under Aggressive Query-Agnostic KV Cache Eviction

Query-agnostic KV cache eviction compresses a context once and reuses the resulting cache for arbitrary future queries, but performance can collapse under tight budgets. Existing methods primarily improve which original

推荐理由RestoreKV: Recovering Full-Cache:Query-agnostic KV cache eviction compresses a context once and reuses the resulting。
模型与评测HF daily papers