14 papers
Beyond the Teacher: Understanding and Preserving Distillation Overshoot in Agentic On-Policy Distillation
Jike Zhong, Ming Li, Yuxiang Lai +9
On-policy distillation (OPD) trains agents on their own trajectories using supervision from a stronger teacher. We uncover a counterintuitive phenomenon in multi-turn agentic tasks…
DeLoop: Repeated Actions as Self-Supervision for Long-Horizon Agents
Tianle Chen, Pushkar Singh, Ketan Todi +8
Language-model agents that run long tasks often redo work they have already done: they re-issue a tool call they made earlier and get back exactly the same observation, a step that…
DTDD: Divergence-Triggered Dynamic Distillation for Reliable On-Policy Supervision
Qijia He, Zequn Li, Spencer Luo +6
On-policy distillation (OPD) provides dense token-level supervision on student rollouts, but this supervision can become unreliable when the student and teacher diverge, either bec…
Improving LLM Collaboration via Multi-Agent Preference Learning
Shuo Liu, Xinzichen Li, Tianle Chen +1
Several works have explored multi-agent reinforcement learning (MARL) in LLM collaboration. However, constructing reliable rewards is difficult in practice, as complete and accurat…
Fewer Tokens, Smaller Cache: Reward-Coordinated Efficient Reasoning
Qiyuan Zhu, Dezhi Li, Pengyu Cheng +8
Large Reasoning Models (LRMs) excel on complex tasks through long chain-of-thought (CoT) reasoning, but their lengthy intermediate steps cause severe overthinking that inflates inf…
The Curse of Helpfulness: Inverse Scaling Law in Robustness to Distractor Instructions via DistractionIF
Zeli Su, Zhankai Xu, Tianlei Chen +4
Large Language Models (LLMs) are increasingly deployed in agentic and retrieval-augmented generation (RAG) systems, where they must execute user-specified tasks over externally pro…
Counteraction-Aware Multi-Teacher On-Policy Distillation for General Capability Recovery with Domain Preservation
Tianlei Chen, Jiao Ou, Ziyuan Liu +3
Domain specialization can improve LLM behavior, but often weakens the general capabilities inherited from the original model. Recent Multi-Teacher On-Policy Distillation (MOPD) pip…
A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoning
Tianle Chen, Deepti Ghadiyaram
As audio-visual multi-modal large language models (MLLMs) are increasingly deployed in safety-critical applications, understanding their cross-modal vulnerabilities is essential. T…
VLM-UQBench: A Benchmark for Modality-Specific and Cross-Modality Uncertainties in Vision Language Models
Chenyu Wang, Tianle Chen, H. M. Sabbir Ahmad +2
Uncertainty quantification (UQ) is vital for ensuring that vision-language models (VLMs) behave safely and reliably. A central challenge is to localize uncertainty to its source, d…
Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
Shuo Liu, Tianle Chen, Ryan Amiri +1
Recent work has explored optimizing LLM collaboration through Multi-Agent Reinforcement Learning (MARL). However, most MARL fine-tuning approaches rely on predefined execution prot…
Some Modalities are More Equal Than Others: Decoding and Architecting Multimodal Integration in MLLMs
Tianle Chen, Chaitanya Chakka, Arjun Reddy Akula +2
Despite remarkable advancements in Multimodal Large Language Models (MLLMs), a fundamental question remains: are MLLMs robust to contradicting modalities? To rigorously study this,…
EEE-Bench: A Comprehensive Multimodal Electrical And Electronics Engineering Benchmark
Ming Li, Jike Zhong, Tianle Chen +2
Recent studies on large language models (LLMs) and large multimodal models (LMMs) have demonstrated promising skills in various domains including science and mathematics. However,…
Counterfactual Explainable Incremental Prompt Attack Analysis on Large Language Models
Dong Shu, Mingyu Jin, Tianle Chen +2
This study sheds light on the imperative need to bolster safety and privacy measures in large language models (LLMs), such as GPT-4 and LLaMA-2, by identifying and mitigating their…
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Dong Shu, Tianle Chen, Mingyu Jin +3
The task of multi-hop link prediction within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, as it requires the model to reason through and u…