3 accepted papers
Multimodal reasoning is a dynamic process that requires synergistic coordination of language and vision. However, current approaches to multimodal interleaved generation fall short of providing a generalizable recipe that productively engages text and vision to advance reasoning. We introduce ThinkM…
The ability to organically reason over and with both text and images is a pillar of human intelligence, yet the ability of Multimodal Large Language Models (MLLMs) to perform such multimodal reasoning remains under-explored. Existing benchmarks often emphasize text-dominant reasoning or rely on shal…
Recent researches have shown that Large Language Models (LLMs) are susceptible to a security threat known as Backdoor Attack. The backdoored model will behave well in normal cases but exhibit malicious behaviours on inputs inserted with a specific backdoor trigger. Current backdoor studies on LLMs p…