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Kaile Wang

9 papers hereh-index 9805 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 9 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.CL3
  • cs.LG1
  • q-bio.QM1
same name
  • Kaile Wang — 4 papers, h 10
  • Kaile Wang — 4 papers, h 3
  • Kaile Wang — 3 papers, h 3
  • Kaile Wang — 1 paper
  • Kaile Wang — 1 paper
  • Kaile Wang — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedRAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models

2 citations · 2 across the 7 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2025

AI Deception: Risks, Dynamics, and Controls

Boyuan Chen, Sitong Fang, Jiaming Ji +56

As intelligence increases, so does its shadow. AI deception, in which systems induce false beliefs to secure self-beneficial outcomes, has evolved from a speculative concern to an…

cs.AI2025

Mitigating Deceptive Alignment via Self-Monitoring

Jiaming Ji, Wenqi Chen, Kaile Wang +8

Modern large language models rely on chain-of-thought (CoT) reasoning to achieve impressive performance, yet the same mechanism can amplify deceptive alignment, situations in which…

cs.AI2025

InterMT: Multi-Turn Interleaved Preference Alignment with Human Feedback

Boyuan Chen, Donghai Hong, Jiaming Ji +12

As multimodal large models (MLLMs) continue to advance across challenging tasks, a key question emerges: What essential capabilities are still missing? A critical aspect of human l…

cs.AI2024

Align Anything: Training All-Modality Models to Follow Instructions with Language Feedback

Jiaming Ji, Jiayi Zhou, Hantao Lou +16

Reinforcement learning from human feedback (RLHF) has proven effective in enhancing the instruction-following capabilities of large language models; however, it remains underexplor…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.