11 papers
KUAISHOU Explorer LLM-Rec Challenge 2026: Reasoning Generative Recommendation
Jiangxia Cao, Hao Peng, Wenlong Xu +97
Generative recommendation, has been attracted a surge of attentions in industrial and academic research community, towards to build more smart system to build next-generation recom…
SiLR: Structure-Preserving Admission and Process Reward for LLM Tool Agents
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
A runtime gate for an LLM tool agent is usually cast as a filter. In a ReAct loop a rejected proposal is followed by another at the same state, so the gate is a search operator ove…
Coverage, Not Targeting: A Structural Regime in Multi-Turn Agent Credit Assignment
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
Multi-turn agentic RL increasingly treats credit assignment as a targeting problem: given a terminal verifiable reward, per-turn methods localize credit onto the turns that mattere…
Pixel Decodability Is Not a Compression Signal: Causally Evaluating Importance Proxies for Visual KV-Cache Eviction
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
Vision-language models retain a substantial amount of pixel-decodable visual content in their visual key-value cache. We show, in our setting, that this retention is task-inert: ac…
PLCBench: Can Autonomous LLM Agents Turn PLC Access into Sustained Physical Impact?
Yitian Zhou, Jingyu Zheng, Qiliang Jiang +6
Industrial control systems (ICSs) rely on programmable logic controllers (PLCs) to connect networked computation with physical control. Tool-using large language model (LLM) agents…
Multilingual Verifier Bias in RLVR: Benchmark, Rollout Diagnosis, and the Cross-Lingual Selection Bottleneck
Chenyu Zhou, Qiliang Jiang, Xu Zhou
Reinforcement learning with verifiable rewards (RLVR) is a standard recipe for training large language models on mathematical reasoning, where an answer verifier serves as a langua…
Certified Speculative Execution for Untrusted AI Agents
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
Hard-constrained sequential decision systems have no certified way to spend the test-time compute of modern AI: executing the multi-step drafts of a learned policy or a frozen LLM…
The Verifier is the Curriculum: Precision Sets the Return on Search in Code Self-Distillation
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
Post-training a code generator against a learned judge can optimize proxy features that raise the score without improving the artifact. We study the opposite signal: a deterministi…
Mechanism-Guided Selective Unlearning for RLVR-Induced Reasoning
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
We propose MAST (Mechanism-Aligned Selective Targeting), a mechanism-guided method for unlearning RLVR-induced reasoning with substantially lower collateral damage than standard fu…
Dense Coordinate-List Fine-Tuning Induces a Controllable Interference Surface in Vision-Language Models
Chenyu Zhou, Qiliang Jiang, Boguang Pan
Fine-tuning vision-language models to emit dense coordinate lists improves visual grounding but also changes how models serialize, repeat, and terminate structured outputs. We stud…
The Vision Encoder as a Privacy Boundary: Visual-Token Side Channels in Encoder-Free Vision-Language Models
Chenyu Zhou, Qiliang Jiang, Shuning Wu +1
A vision encoder compresses image pixels into semantic embeddings, implicitly acting as a privacy boundary by preserving semantic content while attenuating pixel-local detail requi…