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11 papers · 1 filter

cs.AI2026

Budgeted KV-Cache Repair for Evolving Contexts

Han Yu, Wenhui Zhu, Jincheng Cao +15

Language-model agents revise their working context as information becomes obsolete, but deleting text does not erase its influence on cached computation. Later key-value (KV) state…

cs.LG2026

AvoKV-E: Payload-Aware KV Cache Eviction for Long Reasoning

Han Yu, Wenhui Zhu, Xiwen Chen +9

Long-output reasoning shifts the KV-cache bottleneck from the fixed prompt to the generated trace. Existing reasoning-cache eviction methods largely treat cached entries as routing…

cs.LG2026

Smaller Models, Better Rejects: Preference Distillation Scaling

Rui Cai, Wenhui Zhu, Xiwen Chen +15

Preference distillation typically treats a teacher response as preferred and the student's own response as rejected. This assumes that self-generated failures are the most informat…

cs.CR2026

Triaging Threats to Specialized Guardrails

Wenjie Jacky Mo, Xiaofei Wen, Rui Cai +6

Building robust safety guardrails is essential for deploying Large Language Models across diverse real-world applications. However, this goal remains challenging because safety ris…

cs.CV2026

When Vision Speaks for Sound

Xiaofei Wen, Wenjie Jacky Mo, Xingyu Fu +6

Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual cues to infer or hallucinate…

cs.LG2026

ModelLens: Finding the Best for Your Task from Myriads of Models

Rui Cai, Weijie Jacky Mo, Xiaofei Wen +5

The open-source model ecosystem now contains hundreds of thousands of pretrained models, yet picking the best model for a new dataset is increasingly infeasible: new models and unb…

cs.CL2026

Your Agent is More Brittle Than You Think: Uncovering Indirect Injection Vulnerabilities in Agentic LLMs

Wenhui Zhu, Xuanzhao Dong, Xiwen Chen +7

The rapid deployment of open-source frameworks has significantly advanced the development of modern multi-agent systems. However, expanded action spaces, including uncontrolled pri…

cs.CL2026

Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization

Qiyao Ma, Dechen Gao, Rui Cai +4

Pluralistic alignment has emerged as a critical frontier in the development of Large Language Models (LLMs), with reward models (RMs) serving as a central mechanism for capturing d…

cs.CL2026

Grounded Token Initialization for New Vocabulary in LMs for Generative Recommendation

Daiwei Chen, Zhoutong Fu, Chengming Jiang +12

Language models (LMs) are increasingly extended with new learnable vocabulary tokens for domain-specific tasks, such as Semantic-ID tokens in generative recommendation. The standar…

cs.CL2026

AriadneMem: Threading the Maze of Lifelong Memory for LLM Agents

Wenhui Zhu, Xiwen Chen, Zhipeng Wang +11

Long-horizon LLM agents require memory systems that remain accurate under fixed context budgets. However, existing systems struggle with two persistent challenges in long-term dial…

cs.CV2026

CARPE: Context-Aware Image Representation Prioritization via Ensemble for Large Vision-Language Models

Donghee Lee, Rui Cai, Zhe Zhao

Large vision-language models (LVLMs) are typically trained using autoregressive language modeling objectives, which align visual representations with linguistic space. While effect…